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 55–72 of 299 launches
AI Developer Tools

Copilot usage metrics review-cycle fields

On July 7, 2026, GitHub added avg_pull_requests_minutes_to_review and avg_pull_requests_review_cycles fields to the totals_by_ai_adoption_phase breakdown in Copilot usage metrics.

Recheck due Free: No API: Yes Open: Unknown
Clear use caseTraction 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: 2026-07-08.
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 added average-minutes-to-review and review-cycle fields to the adoption-phase breakdown in Copilot usage metrics (github.blog). AI Platform Teams and Engineering Leaders measuring whether Copilot…

AI Coding Tools

GitHub Copilot app for all Copilot plans

On July 7, 2026, GitHub announced that the GitHub Copilot app is available on every Copilot plan across macOS, Windows, and Linux.

Recheck due Free: Yes API: Unknown Open: Yes
Clear use caseGitHub tractionTraction signal
Launch readiness
7.3 / 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: 2026-07-08.
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 made the Copilot app available on every plan across macOS, Windows, and Linux — including Copilot Free and GitHub Education (github.blog). Developers, Students,…

AI Coding Tools

Kimi K2.7 Code in GitHub Copilot Business and Enterprise

On July 7, 2026, GitHub made Kimi K2.7 Code available for Copilot Business and Copilot Enterprise plans after the earlier rollout to Pro, Pro+, and Max.

Recheck due Free: No API: Unknown Open: Unknown
Clear use caseTraction signal
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: 2026-07-08.
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 extended Kimi K2.7 Code to Copilot Business and Enterprise plans, following its earlier rollout to Pro, Pro+, and Max (github.blog). AI Platform Teams…

AI Infrastructure

Hugging Face Kernels

Hugging Face published a major Kernels redesign on July 6, 2026, including a first-class Hub repository type for compute kernels, stricter publisher controls, redesigned command-line tools, and broader…

Recheck due Free: Yes API: Yes Open: Yes
Clear use caseGitHub tractionTraction signal
Launch readiness
7.7 / 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: 2026-07-09.
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.

Hugging Face shipped a major Kernels redesign — a first-class Hub repository type for compute kernels, stricter publisher controls, redesigned command-line tools, and broader…

AI Infrastructure

Elastic Training with MaxText

Google published an end-to-end elastic-training workflow for MaxText, Pathways, GKE, and Cloud TPUs on July 6, 2026.

Recheck due Free: Yes API: Yes Open: Yes
Clear use caseGitHub tractionTraction 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: 2026-07-09.
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 published an end-to-end elastic-training workflow for MaxText across Pathways, GKE, and Cloud TPUs, turning a mid-training slice failure into a recoverable event (developers.googleblog.com).…

AI Coding Tools

GitHub Copilot Cost Centers AI Credit Pools

GitHub added AI credit pools to cost centers on July 2, 2026 so eligible enterprises can cap how much included Copilot AI credit usage a group draws from…

Recheck due Free: No API: Yes Open: No
Clear use caseBusiness-friendly
Launch readiness
6.8 / 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: 2026-07-09.
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 added AI credit pools to cost centers, letting eligible enterprises cap how much included Copilot usage a group draws from the shared pool…

AI Coding Tools

GitHub Copilot Agent Session Streaming

GitHub launched a public preview that lets eligible GitHub Enterprise Cloud owners stream Copilot agent session records across supported clients to an audit destination or retrieve the previous…

Recheck due Free: No API: Yes Open: No
Clear use case

GitHub Copilot agent session streaming provides a valuable evidence feed across clients, but it is a public preview with narrow tenant eligibility, a 48-hour…

AI Coding Tools

GitHub Copilot AI Agent Session Limits

GitHub added public-preview AI credit session limits to Copilot CLI and the GitHub Copilot SDK on July 1, 2026.

Recheck due Free: Unknown API: Yes Open: No
Clear use caseDeveloper-friendly
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: 2026-07-09.
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 added public-preview AI credit session limits to Copilot CLI and the SDK, putting a task-level boundary around model, subagent, and background usage in…

AI Agents

Genkit Agents API

Google introduced the Genkit Agents API in preview for TypeScript and Go, with a shared chat interface, streaming, server- or client-managed state, snapshots, human interrupts, detached tasks and…

Recheck due Free: Yes API: Yes Open: Yes
Clear use caseDeveloper-friendlyGitHub tractionTraction 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: 2026-07-28.
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.

Genkit Agents API removes repeated full-stack agent plumbing while leaving teams in control of runtime and state ownership. The preview can introduce breaking changes…

AI Image Tools

Dreamina details Octo creative workflow during closed beta

Dreamina published a dated workflow guide describing how Octo connects conversational planning, a multimodal canvas, image generation and editing, video generation, a timeline and export. This record is…

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

The June 29 guide is useful evidence of Dreamina’s intended Octo workflow, but not proof of a broad release or production reliability. The strongest…

AI Productivity Tools

CubeOne AI Slide Editor

CubeOne introduced AI-assisted slide generation and editing with PowerPoint import and export.

Recheck due Free: Yes API: Unknown Open: Unknown
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: 2026-07-24.
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.

CubeOne introduced AI-assisted slide generation and editing with PowerPoint import and export (getcube.one). Founders, Marketers, and Educators who need prompt-based decks that stay editable…

AI Productivity Tools

Deckwise

Deckwise launched an AI presentation workflow for generating editable decks from topics, notes, files, and source material.

Recheck due Free: Yes API: Unknown Open: Unknown
Clear use case
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: 2026-07-24.
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.

Deckwise launched an AI presentation workflow that generates editable decks from topics, notes, files, and source material, with a public pricing page (deckwise.io). Founders,…

AI Automation Tools

QApilot CoWork

QApilot introduced CoWork for converting manual mobile test cases into executable iOS, Android, and Flutter automation with AI planning and human approval.

Recheck due Free: Unknown API: Unknown Open: Unknown
Clear use case
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: 2026-07-24.
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.

QApilot introduced CoWork, converting manual mobile test cases into executable iOS, Android, and Flutter automation with AI planning and human approval (qapilot.io). Mobile QA…

AI Models

MAI-Code-1-Flash for Copilot Business and Enterprise

GitHub made Microsoft's MAI-Code-1-Flash coding model generally available to Copilot Business and Copilot Enterprise on June 26, 2026.

Recheck due Free: No API: No Open: No
Clear use caseDeveloper-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: 2026-07-09.
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 made Microsoft's MAI-Code-1-Flash generally available to Copilot Business and Enterprise — a coding model tuned for fast iterative work, with reasoning length adapting…

AI Research Tools

note.md Local LLM Memory

note.md updated its local-first macOS research workspace so cited notes and research documentation can serve as private, file-based memory for AI tools.

Recheck due Free: Unknown API: Unknown Open: Unknown
Clear use caseBeginner-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: 2026-07-24.
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.

note.md launched a local-first Mac research workspace that turns cited notes and documentation into local LLM memory for private search, with a public pricing…

AI Coding Tools

GitHub Desktop 3.6 Copilot Integration

GitHub released Desktop 3.6 with Git worktrees, Copilot SDK-based commit authoring, repository instruction support, model selection, bring-your-own-key options and AI-assisted merge-conflict explanations and suggestions.

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

Desktop 3.6 combines three practical improvements—worktrees, better commit assistance and conflict help—without removing the Git review boundary. Worktrees can still share resources, and a…

AI Coding Tools

Copilot Code Review Analysis Depth

GitHub updated Copilot code review on June 25, 2026 with organization defaults and visible attribution for the Medium review-effort preview, plus a new file-exploration path built on Copilot…

Recheck due Free: No API: Yes Open: No
Clear use caseDeveloper-friendly
Launch readiness
6.8 / 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: 2026-07-09.
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 updated Copilot code review with organization defaults, visible attribution for the Medium review-effort preview, and a new file-exploration path built on Copilot CLI…

AI Agents

GitHub Copilot for Jira reaches GA: June 25, 2026 launch record

GitHub Copilot for Jira reached general availability, adding real-time Copilot cloud-agent progress inside Jira, post-session steering and simplified onboarding for connected GitHub repositories.

Recheck due Free: No API: Unknown Open: No
Clear use caseBusiness-friendlyDeveloper-friendly

The GA release closes useful workflow gaps by returning agent progress and follow-up control to Jira. The integration also moves ticket context into a…

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 Hardware

RayNeo iO

Summary: RayNeo announced the iO smart glasses on August 21, 2026. The official product page labels the device as coming September 4; it is an announced product,…

Why it matters: RayNeo iO is a legitimate product announcement with a dated commercial-launch target, but it is not yet a shipping product. Treat hardware, AI-assistant, battery,…

Pricing
The official product page advertises an early-bird offer and an extra discount but does not expose a reliable final product price in the reviewed page text. RayNeo states a September 4 launch; verify regional pricing and shipping status at release.
Verification
Source-verified; 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
Source-verified; 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
Source-verified; 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
Source-verified; 3 sources
AI Assistant

ChatGPT for Teens

Summary: OpenAI announced ChatGPT for Teens on August 18, 2026. Eligible users aged 13 to 17, including accounts the system estimates are under 18, are placed into…

Why it matters: A material ChatGPT update for teens and families because it attaches defined learning features and default protections to a distinct under-18 experience. Kingy has…

Pricing
OpenAI does not list a separate ChatGPT for Teens price. The help documentation says eligible accounts remain active when the teen experience is enabled; plan eligibility, feature limits, and regional rollout can vary and should be checked before relying on access.
Verification
Source-verified; 2 sources
AI Coding Tools

DeepSeek Harness developer preview

Summary: DeepSeek opened the DeepSeek Harness developer preview and published its source code on August 13, 2026. The official landing page and repository describe an agent harness…

Why it matters: This is a substantive launch for developers because DeepSeek published both a runnable package and the source behind a composable agent runtime. Treat it…

Pricing
The source code is published under the MIT License and the documented local start path does not list a purchase price. The reviewed official sources do not advertise a paid hosted tier. Local use requires a compatible Node.js runtime and the user's own model or service costs may still apply.
Verification
Source-verified; 6 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: Treat November 30 as a workflow migration deadline, not a new product launch and not a one-line model swap. Export each workflow, inventory nodes,…

Pricing
There is no separate shutdown or migration fee. Replacement API usage and ChatGPT workspace access follow current OpenAI pricing; engineering, evaluation, observability and rollback work remain implementation costs.
Verification
Recheck due; 5 sources
AI Developer Tools

OpenAI GPT Image API shutdown deadline: 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: Treat December 1 as a production migration deadline, not an image-model launch. Change the pinned model ID in a test environment, then compare output…

Pricing
There is no separate migration fee. GPT Image 2 is billed under current API token pricing, which varies with text and image input, output, size and quality; teams should remeasure cost on representative jobs rather than carry forward old per-image assumptions.
Verification
Recheck due; 4 sources
Explore launch categories, methodology and participation Awards archive, category paths, methodology, submissions, sponsorship and newsletter

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

Sponsor Kingy AI launch coverage

Launching an AI product that needs clear demos, creator education, and buyer trust? Sponsor a Kingy AI video or launch feature.

Brief status

The Kingy Brief

One consequential launch, one pricing, limit, or shutdown change, one hands-on test, one exact prompt or Test Pack, and one try / watch / skip verdict.