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Verified AI Launch Intelligence

See what launched, what changed, and what it costs.

Track AI product launches, model updates, pricing changes and tested workflows. Each record separates official sources, company claims, Kingy testing and third-party evidence so you can see what is known and what remains unverified.

Launch tracker

Browse the AI Launch Tracker

Search source-backed launch records, then use common filters first and advanced filters only when you need a narrower view.

Server-rendered fallback. Checking the live launch index…
Showing 37–54 of 89 launches
AI Agents

Replit Agent adds custom Shopify storefront creation

Replit added a Shopify workflow where users can design and launch a custom storefront by chatting with Replit Agent, including generating a front end, creating a Shopify store,…

Recheck due Free: Yes API: No Open: No
Clear use caseVideo demoBeginner-friendlyCreator-friendly
Launch readiness
6.5 / 10
Demo evidence
Not scored yet
Creator-story fit
Not scored yet
Score definitions and rubric

These are launch-record readiness heuristics, not product ratings.

Launch readiness

How complete and reviewable the launch record is, not the quality of the product.

Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.

Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.

Demo evidence

Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.

Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.

Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.

Creator-story fit

Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.

Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.

Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.

Scale
0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
Assigned by
Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
Rubric and check date
Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-08.
Confidence and missing data
Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
Freshness
Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
Disputes
Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.

Replit added a Shopify workflow where users design and launch a custom storefront by chatting with Replit Agent — generating the front end, creating…

AI Agents

OpenAI updates GPT-Rosalind with new agentic scientific capabilities

OpenAI introduced new GPT-Rosalind capabilities aimed at improving biological reasoning, bioinformatics, and autonomous scientific workflows.

Recheck due Free: No API: No Open: No
Clear use case
Launch readiness
5.7 / 10
Demo evidence
Not scored yet
Creator-story fit
Not scored yet
Score definitions and rubric

These are launch-record readiness heuristics, not product ratings.

Launch readiness

How complete and reviewable the launch record is, not the quality of the product.

Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.

Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.

Demo evidence

Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.

Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.

Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.

Creator-story fit

Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.

Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.

Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.

Scale
0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
Assigned by
Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
Rubric and check date
Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-08.
Confidence and missing data
Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
Freshness
Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
Disputes
Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.

OpenAI introduced new GPT-Rosalind capabilities aimed at biological reasoning, bioinformatics, and autonomous scientific workflows (openai.com). Biology Researchers and Bioinformatics Teams tracking AI-assisted discovery should…

AI Agents

Replit SEO Agent launches to improve web and AI-search discoverability

Replit introduced SEO Agent, which scans published apps, identifies discoverability issues, and can apply fixes for web search and AI search visibility.

Recheck due Free: Yes API: No Open: No
Clear use caseVideo demoBeginner-friendlyBusiness-friendly
Launch readiness
6.4 / 10
Demo evidence
Not scored yet
Creator-story fit
Not scored yet
Score definitions and rubric

These are launch-record readiness heuristics, not product ratings.

Launch readiness

How complete and reviewable the launch record is, not the quality of the product.

Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.

Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.

Demo evidence

Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.

Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.

Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.

Creator-story fit

Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.

Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.

Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.

Scale
0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
Assigned by
Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
Rubric and check date
Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-08.
Confidence and missing data
Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
Freshness
Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
Disputes
Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.

Replit introduced SEO Agent, which scans published apps, flags discoverability issues, and can apply fixes for web and AI search visibility (replit.com). Replit Builders…

AI Agents

Microsoft Scout launches as an always-on personal Autopilot agent

Microsoft introduced Scout, its first Autopilot agent, designed to stay active in the background, connect across Microsoft 365 apps, and help coordinate work under enterprise controls.

Recheck due Free: No API: No Open: No
Clear use caseVideo demo
Launch readiness
5.9 / 10
Demo evidence
Not scored yet
Creator-story fit
Not scored yet
Score definitions and rubric

These are launch-record readiness heuristics, not product ratings.

Launch readiness

How complete and reviewable the launch record is, not the quality of the product.

Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.

Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.

Demo evidence

Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.

Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.

Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.

Creator-story fit

Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.

Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.

Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.

Scale
0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
Assigned by
Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
Rubric and check date
Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-08.
Confidence and missing data
Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
Freshness
Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
Disputes
Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.

Microsoft introduced Scout, its first Autopilot agent — designed to stay active in the background, connect across Microsoft 365 apps, and coordinate work under…

AI Agents

OpenAI expands Codex for every role, tool, and workflow

OpenAI expanded Codex across roles, tools, and workflows, positioning it as a broader professional agent for software-adjacent and knowledge-work tasks.

Recheck due Free: No API: Yes Open: No
Clear use caseVideo demoCreator-friendlyDeveloper-friendly
Launch readiness
6.1 / 10
Demo evidence
Not scored yet
Creator-story fit
Not scored yet
Score definitions and rubric

These are launch-record readiness heuristics, not product ratings.

Launch readiness

How complete and reviewable the launch record is, not the quality of the product.

Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.

Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.

Demo evidence

Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.

Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.

Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.

Creator-story fit

Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.

Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.

Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.

Scale
0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
Assigned by
Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
Rubric and check date
Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-08.
Confidence and missing data
Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
Freshness
Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
Disputes
Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.

OpenAI expanded Codex across roles, tools, and workflows, positioning it as a broader professional agent for software-adjacent knowledge work (openai.com). Developers, Product Managers, Data…

AI Agents

CoSupport AI 2.0 adds decision logs and action-capable support workflows

CoSupport says version 2.0 replaces its earlier single-pass retrieval flow with multi-step search and validation. The update adds per-reply decision logs, an Agentic API for actions in connected…

Unknown Free: No API: Yes Open: No
Product Hunt tractionClear use caseVideo demoBusiness-friendly

Watch. CoSupport AI 2.0 is a substantive operations-focused update, particularly for teams that need decision visibility and actions through Shopify or Stripe. Its performance,…

AI Agents

OpenAI frontier models and Codex become available on AWS

OpenAI announced that frontier models and Codex are available on AWS, expanding enterprise deployment options for OpenAI-powered agentic workflows.

Recheck due Free: No API: Yes Open: No
Clear use case
Launch readiness
6.2 / 10
Demo evidence
Not scored yet
Creator-story fit
Not scored yet
Score definitions and rubric

These are launch-record readiness heuristics, not product ratings.

Launch readiness

How complete and reviewable the launch record is, not the quality of the product.

Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.

Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.

Demo evidence

Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.

Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.

Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.

Creator-story fit

Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.

Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.

Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.

Scale
0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
Assigned by
Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
Rubric and check date
Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-08.
Confidence and missing data
Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
Freshness
Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
Disputes
Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.

OpenAI announced that its frontier models and Codex are available on AWS, confirmed by both companies' posts (openai.com). Enterprise Platform Teams standardized on AWS…

AI Agents

Vibe gets to work.

Mistral AI relaunched Le Chat as Vibe, a unified agent for long-horizon work and coding with Work Mode, Code Mode, VS Code support, CLI updates, and mobile access.

Recheck due Free: Yes API: Yes Open: No
Clear use caseVideo demoBusiness-friendlyDeveloper-friendly
Launch readiness
7.1 / 10
Demo evidence
Not scored yet
Creator-story fit
Not scored yet
Score definitions and rubric

These are launch-record readiness heuristics, not product ratings.

Launch readiness

How complete and reviewable the launch record is, not the quality of the product.

Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.

Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.

Demo evidence

Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.

Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.

Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.

Creator-story fit

Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.

Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.

Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.

Scale
0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
Assigned by
Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
Rubric and check date
Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-08.
Confidence and missing data
Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
Freshness
Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
Disputes
Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.

Mistral relaunched Le Chat as Vibe, a unified agent for long-horizon work and coding with Work Mode, Code Mode, VS Code support, CLI updates,…

AI Agents

Introducing Claude Opus 4.8

Anthropic released Claude Opus 4.8 with improved coding, agentic task performance, professional work quality, effort controls, and Claude Code dynamic workflows.

Recheck due Free: No API: Yes Open: No
Clear use caseVideo demoBusiness-friendlyDeveloper-friendly
Launch readiness
7.9 / 10
Demo evidence
Not scored yet
Creator-story fit
Not scored yet
Score definitions and rubric

These are launch-record readiness heuristics, not product ratings.

Launch readiness

How complete and reviewable the launch record is, not the quality of the product.

Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.

Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.

Demo evidence

Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.

Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.

Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.

Creator-story fit

Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.

Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.

Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.

Scale
0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
Assigned by
Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
Rubric and check date
Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-08.
Confidence and missing data
Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
Freshness
Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
Disputes
Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.

Anthropic released Claude Opus 4.8 with improved coding, agentic task performance, effort controls, and Claude Code dynamic workflows, priced at $5 per million input…

AI Agents

Cohere launches Command A+ as an open-source model for agentic enterprise workflows

Cohere released Command A+ as an Apache 2.0 open-source MoE model optimized for reasoning, multilingual, multimodal, RAG, and agentic workflows.

Recheck due Free: Yes API: Yes Open: Yes
Clear use caseBusiness-friendlyDeveloper-friendlyTraction signal
Launch readiness
7.2 / 10
Demo evidence
Not scored yet
Creator-story fit
Not scored yet
Score definitions and rubric

These are launch-record readiness heuristics, not product ratings.

Launch readiness

How complete and reviewable the launch record is, not the quality of the product.

Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.

Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.

Demo evidence

Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.

Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.

Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.

Creator-story fit

Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.

Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.

Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.

Scale
0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
Assigned by
Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
Rubric and check date
Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-08.
Confidence and missing data
Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
Freshness
Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
Disputes
Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.

Cohere released Command A+ as an Apache 2.0 open-source MoE model built for reasoning, multilingual, multimodal, RAG, and agentic enterprise workflows (cohere.com). Developers, Enterprises,…

AI Agents

Google introduces Gemini Spark as a 24/7 personal AI agent

Google introduced Gemini Spark as a 24/7 personal AI agent alongside a more agentic Gemini app, Daily Brief, and other I/O 2026 Gemini updates.

Recheck due Free: No API: No Open: No
Clear use caseVideo demo
Launch readiness
6.6 / 10
Demo evidence
Not scored yet
Creator-story fit
Not scored yet
Score definitions and rubric

These are launch-record readiness heuristics, not product ratings.

Launch readiness

How complete and reviewable the launch record is, not the quality of the product.

Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.

Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.

Demo evidence

Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.

Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.

Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.

Creator-story fit

Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.

Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.

Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.

Scale
0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
Assigned by
Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
Rubric and check date
Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-07-10.
Confidence and missing data
Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
Freshness
Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
Disputes
Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.

Google introduced Gemini Spark as a 24/7 personal AI agent alongside a more agentic Gemini app and Daily Brief from I/O 2026 (blog.google). Consumers…

AI Agents

Google launches Managed Agents in the Gemini API

Google launched Managed Agents in the Gemini API, allowing developers to run Antigravity or custom agents in secure Google-hosted Linux sandboxes using markdown-defined instructions and skills.

Recheck due Free: No API: Yes Open: No
Clear use case
Launch readiness
6.7 / 10
Demo evidence
Not scored yet
Creator-story fit
Not scored yet
Score definitions and rubric

These are launch-record readiness heuristics, not product ratings.

Launch readiness

How complete and reviewable the launch record is, not the quality of the product.

Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.

Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.

Demo evidence

Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.

Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.

Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.

Creator-story fit

Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.

Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.

Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.

Scale
0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
Assigned by
Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
Rubric and check date
Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-08.
Confidence and missing data
Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
Freshness
Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
Disputes
Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.

Google launched Managed Agents in the Gemini API, letting developers run Antigravity or custom agents in secure Google-hosted Linux sandboxes using markdown-defined instructions and…

AI Agents

Kiro Web launches autonomous coding workflows from the browser

Kiro launched Kiro Web in preview, letting paid users start browser-based sessions where Kiro can write code, coordinate across repositories, and open pull requests.

Recheck due Free: No API: Yes Open: No
Clear use caseVideo demo
Launch readiness
6.6 / 10
Demo evidence
Not scored yet
Creator-story fit
Not scored yet
Score definitions and rubric

These are launch-record readiness heuristics, not product ratings.

Launch readiness

How complete and reviewable the launch record is, not the quality of the product.

Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.

Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.

Demo evidence

Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.

Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.

Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.

Creator-story fit

Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.

Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.

Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.

Scale
0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
Assigned by
Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
Rubric and check date
Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-08.
Confidence and missing data
Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
Freshness
Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
Disputes
Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.

AWS launched Kiro Web in preview, letting paid users start browser-based sessions where Kiro writes code, coordinates across repositories, and opens pull requests (kiro.dev).…

AI Agents

Cursor Composer 2.5 launches with better sustained long-running agent work

Cursor released Composer 2.5, describing it as a substantial improvement over Composer 2 for sustained long-running tasks, instruction following, and collaboration.

Recheck due Free: No API: No Open: No
Clear use caseVideo demo
Launch readiness
6.2 / 10
Demo evidence
Not scored yet
Creator-story fit
Not scored yet
Score definitions and rubric

These are launch-record readiness heuristics, not product ratings.

Launch readiness

How complete and reviewable the launch record is, not the quality of the product.

Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.

Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.

Demo evidence

Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.

Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.

Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.

Creator-story fit

Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.

Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.

Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.

Scale
0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
Assigned by
Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
Rubric and check date
Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-08.
Confidence and missing data
Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
Freshness
Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
Disputes
Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.

Anysphere released Cursor Composer 2.5, calling it a substantial improvement over Composer 2 for sustained long-running tasks, instruction following, and collaboration (cursor.com). Cursor users…

AI Agents

Advancing voice intelligence with new models in the API

OpenAI released GPT-Realtime-2, GPT-Realtime-Translate, and GPT-Realtime-Whisper for realtime voice reasoning, translation, and streaming transcription in the API.

Recheck due Free: No API: Yes Open: No
Clear use caseBusiness-friendlyDeveloper-friendlyTraction signal

A high-signal API launch because it moves voice AI toward realtime agents that can reason, translate, transcribe, and act during a conversation.

AI Agents

Introducing GPT-5.5

OpenAI released GPT-5.5, a frontier model for agentic coding, computer use, knowledge work, and research workflows across ChatGPT, Codex, and the API.

Recheck due Free: No API: Yes Open: No
Clear use caseBusiness-friendlyDeveloper-friendlyTraction signal
Launch readiness
8.0 / 10
Demo evidence
Not scored yet
Creator-story fit
Not scored yet
Score definitions and rubric

These are launch-record readiness heuristics, not product ratings.

Launch readiness

How complete and reviewable the launch record is, not the quality of the product.

Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.

Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.

Demo evidence

Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.

Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.

Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.

Creator-story fit

Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.

Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.

Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.

Scale
0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
Assigned by
Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
Rubric and check date
Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-08.
Confidence and missing data
Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
Freshness
Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
Disputes
Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.

OpenAI released GPT-5.5, a frontier model for agentic coding, computer use, and research workflows, shipping across ChatGPT, Codex, and the API with documented rates…

AI Agents

Microsoft makes Copilot’s agentic capabilities in Word, Excel, and PowerPoint generally available

Microsoft announced general availability of agentic Copilot capabilities in Word, Excel, and PowerPoint, enabling multi-step, app-native actions inside documents, spreadsheets, and presentations.

Recheck due Free: No API: Yes Open: No
Clear use caseVideo demo

This is a major mainstream agent launch because it brings agentic behavior into Office apps used by billions of people.

AI Agents

OpenAI launches Workspace Agents as a governed research preview

OpenAI introduced Workspace Agents in research preview for ChatGPT Business, Enterprise, Edu and Teachers. Teams can build and share Codex-powered agents with instructions, tools, apps and skills, invoke…

Source-verified Free: No API: Yes Open: No
Clear use case

Workspace Agents matters because it couples repeatable team agents with workspace ownership, permissions and approval controls instead of leaving automation in one employee’s chat.…

Daily radar

Latest verified AI launches

A Radar edition publishes only when the day has enough source-ready signal; the tracker continues to show the newest verified records.

No source-ready records are tagged for today yet, so this section is showing the latest public launch records available in the tracker.

AI Voice/Audio Tools

gamedai live AI sports radio

Summary: gamedai says its live AI sports-radio service went live on August 7, 2026 for the NFL preseason. The launch page describes coverage for all 16 Week…

Why it matters: gamedai is an interesting vertical-agent launch because it joins live data, retrieval, voice generation, and an evaluation layer around one narrow listener job. The…

Pricing
The official homepage lists a free Casual tier, Premium at $9.99 per month with a seven-day free trial, and a $99.99 one-time Lifetime unlock. The reviewed Join Now link returned a deployment-not-found page, so signup and billing availability were not independently confirmed.
Verification
Source-verified; 4 sources
AI Agents

Liquid AI LFM2.5-2.6B

Summary: Liquid AI released the base and post-trained LFM2.5-2.6B checkpoints on August 4, 2026. The post-trained text model targets agentic workloads and ships in native, GGUF, MLX,…

Why it matters: LFM2.5-2.6B is a credible option for high-volume, privacy-sensitive local agents where compact size and tool use matter more than frontier reasoning. Treat it as…

Pricing
The model weights are downloadable under Liquid AI's LFM1.0 license. Liquid AI did not announce a paid hosted API price for this release, and the reviewed Hugging Face page says no inference provider currently deploys the model. Self-hosting avoids a vendor per-token fee but still carries hardware, electricity, engineering, and support costs.
Verification
Source-verified; 5 sources
AI Agents

DeepSeek V4-Flash-0731 launches in API beta with native Codex support

Summary: DeepSeek released DeepSeek-V4-Flash-0731 as the official V4-Flash API public beta. The checkpoint keeps the preview model’s architecture and size but adds new post-training, native Responses API…

Why it matters: Worth testing for cost-sensitive coding-agent workloads because it combines native Codex support, a one-million-token context window, very low API pricing and MIT-licensed weights. Treat…

Pricing
$0.0028 per 1M cached input tokens; $0.14 per 1M uncached input tokens; $0.28 per 1M output tokens. DeepSeek says future peak-hour prices will be 2× regular rates, with no effective date announced.
Verification
Source-verified; 9 sources
AI Coding Tools

OpenAI releases Codex Security CLI and TypeScript SDK in limited beta

Summary: OpenAI published the Codex Security command-line client and TypeScript SDK. The CLI supports repository and change review, bulk scans, history, CI workflows, SARIF output and false-positive…

Why it matters: The CLI and SDK make Codex Security easier to insert into repeatable engineering workflows and expose useful integration primitives such as typed findings, SARIF,…

Pricing
OpenAI does not publish self-serve Codex Security pricing in the reviewed documentation. CLI and SDK access is limited to approved beta customers and partners through an OpenAI account team. Commercial terms, quotas and any Trusted Access for Cyber requirement are account-specific.
Verification
Source-verified; 6 sources
AI Developer Tools

Model Context Protocol 2026-07-28 specification goes final

Summary: The final Model Context Protocol 2026-07-28 specification became the current authoritative protocol version. It replaces connection-level state with self-contained requests, moves capability negotiation to each request…

Why it matters: The 2026-07-28 MCP specification makes a consequential architectural trade: stateless, self-contained requests can simplify scaling and recovery, but implementations must now negotiate and validate…

Pricing
MCP is an open protocol specification, not a paid hosted product. Implementations, infrastructure, models, connectors and support can carry separate costs. The official specification and governance pages are the authority for the protocol boundary.
Verification
Source-verified; 4 sources
AI Security

Microsoft Project Perception

Summary: Microsoft announced Project Perception, an agentic security system that coordinates specialized red, blue, and green agents inside Microsoft Defender.

Why it matters: The launch brings attack simulation, defense testing, and threat-scenario planning into one Microsoft Defender workflow. Its practical effectiveness and cost remain unproven until security…

Pricing
Microsoft says Project Perception uses consumption-based, pay-as-you-go pricing measured in Security Compute Units (SCUs). Different agents consume SCUs at different rates; Microsoft did not publish numeric SCU rates in the checked launch sources.
Verification
Source-verified; 3 sources

Plan ahead

Upcoming Deadlines

Future-dated migration, shutdown, and retirement records are separated from today's launches and latest-record lists. These dates are upcoming operational events, not launches that have already happened.

AI Developer Tools

Google Imagen 4 API shutdown window: August 17, 2026

Summary: Google announced that imagen-4.0-generate-001, imagen-4.0-ultra-generate-001 and imagen-4.0-fast-generate-001 are deprecated. Its deprecations table lists August 17, 2026 as the earliest possible shutdown date and recommends gemini-3.1-flash-image.

Why it matters: Plan against August 17 while preserving Google’s wording: the deprecations page says listed dates are the earliest possible shutdown dates and that exact timing…

Pricing
There is no separate migration fee. Replacement Gemini API image generation follows current Google pricing and quota terms; teams should compare the selected model, image output, prompts and workload mix on the live pricing page.
Verification
Source-verified; 5 sources
AI Agents

OpenAI Assistants API migration deadline: August 26, 2026

Summary: OpenAI’s Assistants API reaches its shutdown deadline on August 26, 2026. OpenAI recommends Responses API and Conversations API, with documented mappings from Assistants to configuration or…

Why it matters: Treat August 26 as an operational deadline, not a feature launch or a find-and-replace exercise. OpenAI documents object and orchestration changes, including explicit tool-loop…

Pricing
There is no separate migration fee. Replacement API usage is billed under current OpenAI API pricing, while engineering, regression testing, data migration, observability and rollback work remain implementation costs.
Verification
Source-verified; 6 sources
AI Developer Tools

Google retires Gemini Robotics ER 1.6 Preview on August 31

Summary: Google announced that gemini-robotics-er-1.6-preview will shut down on August 31, 2026, and its deprecation table names gemini-robotics-er-2-preview as the replacement.

Why it matters: Google announced that gemini-robotics-er-1.6-preview will shut down on August 31, 2026, and its deprecation table names gemini-robotics-er-2-preview as the replacement. Kingy’s action: Replace the…

Pricing
No pricing change announced
Verification
Source-verified; 2 sources

Awards archive

Launches of the Week is paused

Prior editions remain available as an archive. Kingy is not currently promising a new weekly awards edition.

Category navigation

Find AI launches by market, workflow, and source signal

Methodology

How Kingy AI Scores Launches

Kingy AI scoring is designed for launch discovery, editorial review, creator planning, and buyer trust checks.

Kingy score

A directional editorial score for launch clarity, source quality, audience fit, pricing visibility, demo usefulness, and practical buyer or creator value.

Demo score

A signal for whether the product can be shown, tested, explained, or compared without relying on vague announcement copy.

YouTube potential

A creator-fit signal for demos, tutorials, before-and-after workflows, explainers, reviews, and audience-specific product education.

Source verification

Records distinguish verified, needs verification, and founder submitted status using official URLs, source links, last-verified dates, and correction paths.

Pricing clarity

Pricing signals favor launches with visible pricing, free-plan status, pricing pages, API access notes, or clear uncertainty when pricing is not public.

Use-case clarity

Launches are easier to evaluate when the audience, workflow, category, demo, and alternative comparison are obvious from public sources.

Founder and sponsor fit

Founder submissions and sponsor interest are routing signals only; editorial review still checks source quality, public claims, demo clarity, and usefulness.

Verification labels

Verified means enough public source evidence is present, needs verification means the record needs more checking, and founder submitted means the entry came through the submission path.

Scores are editorial signals, not scientific benchmarks, paid placements, or guarantees.

Founder submission

Submit Your AI Launch

Founders can send a launch for editorial review when the public source trail is ready to verify.

What to include

  • Product name
  • Website
  • Launch date
  • What launched
  • Official source links
  • Pricing page
  • Demo/video
  • Company info
  • Category
  • Public funding info
  • Screenshots/media

Privacy note

Do not submit secrets, unreleased financials, private customer data, or regulated personal data.

Submit only public product, company, source, pricing, demo, and media details that Kingy AI can review without logging into private systems.

Sponsor path

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Brief status

The Kingy Brief

Source-checked AI launch and product intelligence. See the public archive for the latest edition and cadence.