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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.

Editorial submissions and sponsor-fit reviews are separate. Payment does not influence Kingy scores, verdicts, rankings, evidence labels, or publication decisions.

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 73–88 of 88 launches
AI Agents

Claude Sonnet 4.5 launches with major coding-agent and computer-use gains

Anthropic released Claude Sonnet 4.5, positioning it as a top model for coding, complex agents, and computer use while also launching related Claude Code and Agent SDK upgrades.

Recheck due Free: No API: Yes Open: No
Clear use caseDeveloper-friendly

A high-signal model release for agents because Anthropic explicitly tied it to coding, computer use, and the Claude Agent SDK.

AI Agents

Replit Agent 3 adds browser self-testing, longer autonomous runs, and agent generation

Replit launched Agent 3 with app testing in a real browser, autonomous work up to 200 minutes, and the ability to build agents and automations.

Recheck due Free: Yes API: No Open: No
Clear use caseVideo demoBeginner-friendlyBusiness-friendly

This was a meaningful autonomy jump because Replit paired generation with real browser self-testing and longer run time.

AI Agents

GitHub Agents Panel launches Copilot coding agent tasks anywhere on GitHub

GitHub added an Agents Panel so users can launch and monitor Copilot coding agent tasks from anywhere on GitHub rather than only from issues.

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

A practical workflow launch: the value is not a new model, but making the coding agent easier to delegate to and supervise inside GitHub.

AI Agents

Introducing ChatGPT agent

OpenAI introduced ChatGPT agent as a unified agentic system combining research, browser action, code execution, and connected app workflows.

Recheck due Free: No API: No Open: No
Clear use caseBeginner-friendlyBusiness-friendlyTraction signal

A key agent-era launch because it reframed ChatGPT as a task executor rather than only a chat interface.

AI Agents

Kiro preview release

Kiro launched in preview as an agentic IDE focused on spec-driven development and AI-assisted software delivery.

Recheck due Free: Yes API: No Open: No
Clear use caseVideo demoDeveloper-friendlyTraction signal
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.

Kiro launched in preview as an agentic IDE focused on spec-driven development — specs, hooks, and AI-assisted delivery — marking AWS's entry into the…

AI Agents

Build AI agents with the Mistral Agents API

Mistral AI launched an Agents API with built-in connectors for code execution, web search, image generation, MCP tools, memory, and orchestration.

Recheck due Free: No API: Yes Open: No
Clear use caseVideo demoBusiness-friendlyDeveloper-friendly

Mistral launched its Agents API in May 2025 with built-in code execution, web search, image generation, MCP tools, persistent memory, and multi-agent orchestration. It…

AI Agents

Introducing OpenAI o3 and o4-mini

OpenAI released o3 and o4-mini, reasoning models designed to solve harder multi-step tasks and use tools such as web search, Python, file analysis, vision, and image generation.

Recheck due Free: Yes API: Yes Open: No
Clear use caseBusiness-friendlyDeveloper-friendlyTraction signal
Launch readiness
7.6 / 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.

OpenAI released o3 and o4-mini, reasoning models built to solve harder multi-step tasks while using tools like web search, Python, file analysis, vision, and…

AI Agents

Grok 3 Beta – The Age of Reasoning Agents

xAI unveiled Grok 3 beta and Grok 3 mini, positioning the release around reasoning, coding, math, world knowledge, and agent-style behavior.

Recheck due Free: No API: Yes Open: No
Clear use caseVideo demoDeveloper-friendlyTraction signal
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.

xAI unveiled Grok 3 beta and Grok 3 mini, positioned around reasoning, coding, math, world knowledge, and agent-style behavior (x.ai). The record describes a…

AI Agents

Zapier AI Agents launch

Zapier introduced AI agents that can work across connected business apps and automate delegated tasks.

Recheck due Free: Yes API: Yes Open: No
Clear use caseVideo demoBeginner-friendlyBusiness-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: 2026-06-24.
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.

Zapier introduced AI agents that work across its connected business apps, automating delegated tasks through the integration network teams already use (zapier.com). Automation Teams,…

AI Agents

Introducing Gemini 2.0

Google introduced Gemini 2.0 as a model family for the agentic era, with native multimodality, tool use, Project Astra, Project Mariner, Jules, and Gemini Deep Research.

Recheck due Free: Yes API: Yes Open: No
Clear use caseBusiness-friendlyDeveloper-friendlyTraction signal
Launch readiness
7.8 / 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 2.0 as a model family for the agentic era — native multimodality and tool use, shipped first as a Flash experimental…

AI Agents

Introducing multi-agent collaboration capability for Amazon Bedrock

AWS introduced a preview capability for Amazon Bedrock that lets multiple agents collaborate on complex tasks.

Recheck due Free: No API: Yes Open: No
Clear use caseBusiness-friendlyDeveloper-friendlyTraction signal
Launch readiness
7.0 / 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.

AWS introduced a preview capability for Amazon Bedrock letting multiple agents collaborate on complex tasks (aws.amazon.com). Enterprises and Automation Teams got a more governed…

AI Agents

Introducing Microsoft Azure AI Foundry

Microsoft unveiled Azure AI Foundry as a unified application platform for designing, customizing, managing, and governing AI solutions.

Recheck due Free: No API: Yes Open: No
Clear use caseVideo demoBusiness-friendlyDeveloper-friendly
Launch readiness
6.9 / 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 unveiled Azure AI Foundry, a unified platform for designing, customizing, managing, and governing AI applications, live at ai.azure.com (azure.microsoft.com). AI Engineers, Developers, and…

AI Agents

Windsurf Launch

Codeium launched the Windsurf Editor as an agentic IDE built around AI flows and the Cascade assistant.

Recheck due Free: Yes API: No Open: No
Clear use caseVideo demoDeveloper-friendlyTraction signal
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.

Codeium launched the Windsurf Editor, an agentic IDE built around AI flows and the Cascade assistant with real-time codebase context, free at launch with…

AI Agents

New autonomous agents scale your team like never before

Microsoft announced public-preview plans for autonomous agents in Copilot Studio and introduced new Dynamics 365 autonomous agents.

Recheck due Free: No API: Yes Open: No
Clear use caseBusiness-friendlyTraction signal
Launch readiness
6.3 / 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 announced public-preview plans for autonomous agents in Copilot Studio and introduced new Dynamics 365 autonomous agents, putting enterprise agents inside its business-software distribution…

AI Agents

Relay.app AI Agent steps launch

Relay.app launched AI Agent steps, DALL-E integration, data formatting steps, and expanded integrations for workflow automation.

Recheck due Free: Yes API: No Open: No
Clear use caseVideo demoBeginner-friendlyBusiness-friendly
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: 2026-06-24.
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.

Relay.app shipped AI Agent steps alongside DALL-E integration, data formatting, and expanded integrations in its June 2024 product update (relay.app). Operators, Small Teams, and…

AI Agents

GitHub Copilot Workspace technical preview

GitHub launched Copilot Workspace in technical preview as a Copilot-native environment for moving from issue or idea to plan and code.

Recheck due Free: Yes API: No Open: No
Clear use caseDeveloper-friendlyTraction signal
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.

GitHub launched Copilot Workspace in technical preview as a Copilot-native environment for moving from an issue or idea to a plan and code (github.blog).…

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 Models

GPT-6 Sol

Summary: OpenAI added GPT-6 Sol to the API as gpt-6-sol and began rolling it out in ChatGPT Work and Codex to eligible paid plans on September 22,…

Why it matters: GPT-6 Sol merits a workload-specific trial when Astra costs more than the task warrants. Kingy's September 22 comparison finds lower cost per task on…

Pricing
OpenAI lists standard direct API rates of US$2 per million input tokens and US$10 per million output tokens for requests with at most 272K input tokens, checked September 22, 2026. Longer context, caching and processing tiers have different rates; consult the official model pricing.
Verification
Source-verified; 3 sources
AI Models

GPT-6 Astra

Summary: OpenAI announced GPT-6 Astra on September 3, 2026. Its release describes a staged rollout to ChatGPT Plus, Pro, Business and Enterprise, the OpenAI API, Microsoft Azure…

Why it matters: Astra is worth evaluating for complex coding, research and computer-use workflows where a failed step is expensive. Its documented tool support is useful, but…

Pricing
OpenAI Standard API rates per million tokens are $10 input, $1 cached input, $12.50 cache writes and $50 output. Above 272,000 input tokens, the full request costs 2× input/cache rates and 1.5× output. Batch/Flex use 50% of Standard rates; Fast uses 2× applicable rates. Tool fees can add to token charges.
Verification
Source-verified; 3 sources
AI Hardware

RayNeo iO

Summary: Announced August 21, 2026, RayNeo iO is now orderable on the official USD storefront. RayNeo says the Polar Night version is expected to begin shipping gradually…

Why it matters: Paid coverage: RayNeo paid Kingy for the September 9 video. No affiliate compensation, supplied product or access, or other benefit was received. Work began…

Pricing
Vendor price checked September 12, 2026: the official USD store lists iO from $449, with a displayed regular price from $499. RayNeo AI and Gemini 3.1 Flash Lite are included free with the product; optional access to other AI models costs US$9.99/month. Confirm the selected variant, destination, accessories, taxes and dispatch estimate at checkout.
Verification
Recheck due; 3 sources
AI Marketing

Attentive AI Grow

Summary: Attentive announced the general availability of AI Grow on August 19, 2026. The product analyzes browsing and shopping behavior among identified and logged-out visitors to decide…

Why it matters: AI Grow is a commercially relevant launch because it applies AI to an established subscriber-acquisition workflow, is generally available, and is measured with cohort-level…

Pricing
Attentive does not publish AI Grow list pricing in the reviewed launch materials. The product is available to Attentive customers through a sales or demo path.
Verification
Recheck due; 2 sources
Enterprise AI

WethosAI Twins

Summary: WethosAI launched Twins on August 18, 2026 as part of its Human Context Platform. The company says organizations can use the capability through its SaaS product,…

Why it matters: Twins is an intriguing enterprise decision-rehearsal launch because WethosAI states explicit permission, access-control, and non-impersonation boundaries. The vendor has not published independent predictive-validity evidence…

Pricing
Public list pricing was not disclosed in the reviewed launch materials. WethosAI offers a request-a-briefing or demo path for the SaaS platform and enterprise/API use.
Verification
Recheck due; 3 sources
AI Infrastructure

Cerebras CS-4

Summary: Cerebras introduced CS-4 on August 18, 2026. The company describes a redesigned rack-scale system using three WSE-3 Turbo processors, a modular Nexus platform, native disaggregated-inference support,…

Why it matters: Cerebras CS-4 is a consequential AI-infrastructure launch with a concrete shipment window and architectural changes beyond a processor refresh. Its headline speed, throughput, and…

Pricing
Public list pricing was not disclosed in the reviewed launch sources. Cerebras directs buyers to contact sales, and the company says first shipments begin this quarter.
Verification
Recheck due; 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 Agents

OpenAI Agent Builder shutdown deadline: November 30, 2026

Summary: OpenAI announced the Agent Builder lifecycle deadline: the visual workflow builder is deprecated and scheduled to shut down on November 30, 2026. OpenAI documents two migration…

Why it matters: Export the workflow, select the Agents SDK or a suitable Workspace Agent, and test tools, state, permissions and guardrails before the November 30 shutdown.…

Pricing
Review replacement API costs or Workspace Agent plan requirements before migrating. This record does not estimate your workflow’s implementation or operating cost.
Verification
Source-verified; 3 sources
AI Developer Tools

Three GPT Image API models are scheduled to retire December 1, 2026

Summary: OpenAI announced an API lifecycle deadline for gpt-image-1-mini, gpt-image-1.5 and chatgpt-image-latest. Those model IDs are scheduled to shut down on December 1, 2026, with gpt-image-2 listed…

Why it matters: OpenAI schedules gpt-image-1-mini, gpt-image-1.5 and chatgpt-image-latest for API removal on December 1, 2026. Its deprecation table names gpt-image-2 as the replacement. Inventory the three…

Pricing
Review the current price of the chosen replacement and measure representative jobs. This lifecycle record does not establish workload cost or promise a cost-neutral migration.
Verification
Source-verified; 5 sources
Explore launch categories, methodology and participation Awards archive, category paths, methodology, submissions, sponsorship and newsletter

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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.

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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

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