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.
Cohere launches Command A+ as an open-source model for agentic enterprise workflows
Cohere released Command A+ as an Apache 2.0 open-source MoE model optimized for reasoning, multilingual, multimodal, RAG, and agentic workflows.
- Launch readiness
- 7.2 / 10
- Demo evidence
- Not scored yet
- Creator-story fit
- Not scored yet
Score definitions and rubric
These are launch-record readiness heuristics, not product ratings.
Launch readiness
How complete and reviewable the launch record is, not the quality of the product.
Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.
Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.
Demo evidence
Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.
Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.
Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.
Creator-story fit
Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.
Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.
Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.
- Scale
- 0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
- Assigned by
- Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
- Rubric and check date
- Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-08.
- Confidence and missing data
- Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
- Freshness
- Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
- Disputes
- Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.
Cohere released Command A+ as an Apache 2.0 open-source MoE model built for reasoning, multilingual, multimodal, RAG, and agentic enterprise workflows (cohere.com). Developers, Enterprises,…
Google introduces Gemini Spark as a 24/7 personal AI agent
Google introduced Gemini Spark as a 24/7 personal AI agent alongside a more agentic Gemini app, Daily Brief, and other I/O 2026 Gemini updates.
- Launch readiness
- 6.6 / 10
- Demo evidence
- Not scored yet
- Creator-story fit
- Not scored yet
Score definitions and rubric
These are launch-record readiness heuristics, not product ratings.
Launch readiness
How complete and reviewable the launch record is, not the quality of the product.
Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.
Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.
Demo evidence
Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.
Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.
Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.
Creator-story fit
Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.
Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.
Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.
- Scale
- 0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
- Assigned by
- Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
- Rubric and check date
- Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-07-10.
- Confidence and missing data
- Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
- Freshness
- Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
- Disputes
- Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.
Google introduced Gemini Spark as a 24/7 personal AI agent alongside a more agentic Gemini app and Daily Brief from I/O 2026 (blog.google). Consumers…
Google launches Managed Agents in the Gemini API
Google launched Managed Agents in the Gemini API, allowing developers to run Antigravity or custom agents in secure Google-hosted Linux sandboxes using markdown-defined instructions and skills.
- Launch readiness
- 6.7 / 10
- Demo evidence
- Not scored yet
- Creator-story fit
- Not scored yet
Score definitions and rubric
These are launch-record readiness heuristics, not product ratings.
Launch readiness
How complete and reviewable the launch record is, not the quality of the product.
Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.
Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.
Demo evidence
Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.
Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.
Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.
Creator-story fit
Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.
Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.
Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.
- Scale
- 0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
- Assigned by
- Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
- Rubric and check date
- Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-08.
- Confidence and missing data
- Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
- Freshness
- Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
- Disputes
- Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.
Google launched Managed Agents in the Gemini API, letting developers run Antigravity or custom agents in secure Google-hosted Linux sandboxes using markdown-defined instructions and…
Kiro Web launches autonomous coding workflows from the browser
Kiro launched Kiro Web in preview, letting paid users start browser-based sessions where Kiro can write code, coordinate across repositories, and open pull requests.
- Launch readiness
- 6.6 / 10
- Demo evidence
- Not scored yet
- Creator-story fit
- Not scored yet
Score definitions and rubric
These are launch-record readiness heuristics, not product ratings.
Launch readiness
How complete and reviewable the launch record is, not the quality of the product.
Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.
Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.
Demo evidence
Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.
Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.
Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.
Creator-story fit
Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.
Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.
Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.
- Scale
- 0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
- Assigned by
- Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
- Rubric and check date
- Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-08.
- Confidence and missing data
- Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
- Freshness
- Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
- Disputes
- Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.
AWS launched Kiro Web in preview, letting paid users start browser-based sessions where Kiro writes code, coordinates across repositories, and opens pull requests (kiro.dev).…
Cursor Composer 2.5 launches with better sustained long-running agent work
Cursor released Composer 2.5, describing it as a substantial improvement over Composer 2 for sustained long-running tasks, instruction following, and collaboration.
- Launch readiness
- 6.2 / 10
- Demo evidence
- Not scored yet
- Creator-story fit
- Not scored yet
Score definitions and rubric
These are launch-record readiness heuristics, not product ratings.
Launch readiness
How complete and reviewable the launch record is, not the quality of the product.
Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.
Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.
Demo evidence
Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.
Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.
Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.
Creator-story fit
Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.
Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.
Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.
- Scale
- 0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
- Assigned by
- Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
- Rubric and check date
- Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-08.
- Confidence and missing data
- Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
- Freshness
- Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
- Disputes
- Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.
Anysphere released Cursor Composer 2.5, calling it a substantial improvement over Composer 2 for sustained long-running tasks, instruction following, and collaboration (cursor.com). Cursor users…
Advancing voice intelligence with new models in the API
OpenAI released GPT-Realtime-2, GPT-Realtime-Translate, and GPT-Realtime-Whisper for realtime voice reasoning, translation, and streaming transcription in the API.
A high-signal API launch because it moves voice AI toward realtime agents that can reason, translate, transcribe, and act during a conversation.
HeyGen April 2026 product update
HeyGen published its April 2026 product update covering advanced avatar, video automation, and AI video workflow improvements.
- 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: 2026-06-24.
- 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.
HeyGen published its April 2026 product update, rounding up advanced avatar, video automation, and AI workflow improvements (heygen.com). Marketers, Sales Teams, and Creators producing…
Otter Conversational Knowledge Engine launch
Otter.ai launched a Conversational Knowledge Engine with AI Chat, desktop capture, and agentic workflow capabilities.
- 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: 2026-06-24.
- 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.
Otter.ai launched its Conversational Knowledge Engine, adding AI Chat, desktop capture, and agentic workflow capabilities on top of its meeting-notes core (otter.ai). Sales Teams,…
Introducing GPT-5.5
OpenAI released GPT-5.5, a frontier model for agentic coding, computer use, knowledge work, and research workflows across ChatGPT, Codex, and the API.
- Launch readiness
- 8.0 / 10
- Demo evidence
- Not scored yet
- Creator-story fit
- Not scored yet
Score definitions and rubric
These are launch-record readiness heuristics, not product ratings.
Launch readiness
How complete and reviewable the launch record is, not the quality of the product.
Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.
Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.
Demo evidence
Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.
Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.
Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.
Creator-story fit
Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.
Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.
Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.
- Scale
- 0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
- Assigned by
- Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
- Rubric and check date
- Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-08.
- Confidence and missing data
- Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
- Freshness
- Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
- Disputes
- Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.
OpenAI released GPT-5.5, a frontier model for agentic coding, computer use, and research workflows, shipping across ChatGPT, Codex, and the API with documented rates…
Microsoft makes Copilot’s agentic capabilities in Word, Excel, and PowerPoint generally available
Microsoft announced general availability of agentic Copilot capabilities in Word, Excel, and PowerPoint, enabling multi-step, app-native actions inside documents, spreadsheets, and presentations.
This is a major mainstream agent launch because it brings agentic behavior into Office apps used by billions of people.
OpenAI launches Workspace Agents as a governed research preview
OpenAI introduced Workspace Agents in research preview for ChatGPT Business, Enterprise, Edu and Teachers. Teams can build and share Codex-powered agents with instructions, tools, apps and skills, invoke…
Workspace Agents matters because it couples repeatable team agents with workspace ownership, permissions and approval controls instead of leaving automation in one employee’s chat.…
Google launches Deep Research and Deep Research Max agents in Gemini API
Google introduced Deep Research and Deep Research Max in the Gemini API with MCP support, native visualizations, planning controls, and richer long-horizon research workflows.
This is a major research-agent launch because Google exposed long-horizon research as a developer-facing agent, not just an app feature.
Claude Opus 4.7 launches as an Anthropic frontier model update for agent work
Anthropic released Claude Opus 4.7 as a frontier Claude update relevant to demanding coding, reasoning, and agentic tasks.
A frontier Claude release is relevant to the agent market because high-capability models determine what long-running agents can reliably complete.
Introducing GPT-Rosalind for life sciences research
OpenAI introduced GPT-Rosalind, a purpose-built frontier reasoning model for biology, drug discovery, translational medicine, and scientific workflows.
- 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.
OpenAI introduced GPT-Rosalind, a purpose-built frontier reasoning model for biology, drug discovery, translational medicine, and scientific workflows (openai.com). Qualified Life Sciences Organizations, Biotech Teams,…
Introducing Forge
Mistral AI introduced Forge, an enterprise system for building frontier-grade AI models grounded in proprietary institutional knowledge.
- Launch readiness
- 6.0 / 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.
Mistral AI introduced Forge, an enterprise system for building frontier-grade AI models grounded in proprietary institutional knowledge (mistral.ai). Enterprises and AI Platform Teams that…
Replit Agent 4 launches as a faster creative app-building agent
Replit introduced Agent 4 as its faster, more versatile app-building agent with creative workflows, design canvas, planning, parallel tasks, collaboration, and integrations.
Agent 4 is important because it pushes Replit further from coding assistant toward agent-first app creation.
Microsoft announces Agent 365 general availability as an AI agent control plane
Microsoft announced Microsoft Agent 365, a control plane for observing, governing, managing, and securing AI agents across organizations, with GA planned for May 1, 2026.
This is one of the clearest signs that agent governance is becoming a standalone enterprise software category.
Apollo MCP in Claude beta launch
Apollo announced that Apollo could power outbound execution in Claude via its native MCP server beta for paid plans.
- 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: 2026-06-24.
- 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.
Apollo announced that its native MCP server beta lets paid-plan users power outbound execution inside Claude — prospecting and outreach without leaving the assistant…
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.
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
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
- Source-verified; 3 sources
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
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
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
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
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.
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
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: Inventory calls to the three retiring IDs. Test the documented gpt-image-2 replacement using its supported endpoint and parameters, then compare generation, edits and cost…
- 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; 4 sources
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Launches are easier to evaluate when the audience, workflow, category, demo, and alternative comparison are obvious from public sources.
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Scores are editorial signals, not scientific benchmarks, paid placements, or guarantees.
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