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…
Microsoft introduced Copilot Managed Runtime’s host and SDK in public preview, with governed code execution inside a Microsoft 365 tenant. This is a separate record from Home, Code…
Managed Runtime gives enterprise builders a preview path for hosting code under tenant controls. Check the host, SDK and admin requirements before planning deployment;…
A box is a persistent Ubuntu machine with SSH and SCP access, Docker, a dedicated IPv4 address, a virtual desktop, snapshots, and disk-level forking. The official docs provide…
box by ASCII addresses a concrete need: Long-running and parallel coding agents need isolated computers with persistent state. The main limitation is this: The…
BaseRT’s second Product Hunt launch appeared on July 19, presenting a one-command local LLM runtime for Apple Silicon after the BaseRT 0.1.6 engine release on July 18.
Recheck dueFree: YesAPI: YesOpen: Unknown
Clear use caseBeginner-friendlyDeveloper-friendlyGitHub traction
BaseRT is a focused option for developers who want Apple Silicon inference behind familiar CLI and OpenAI-compatible interfaces. Its practical value depends on model…
Latitude launched V2 for AI-agent monitoring, combining production traces, session search, behavior-pattern signals, recurring-failure discovery, alerts and a coding-agent handoff supplied with issue context.
Recheck dueFree: YesAPI: YesOpen: 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%.
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.
Latitude V2 creates a useful closed loop from production traces to recurring-failure signals and a proposed repair. Kingy did not connect telemetry, measure cluster…
Cloudflare added 60-minute Temporary Accounts to Wrangler so an unauthenticated coding agent can deploy and revise supported Workers resources, return a preview and claim URL, and let a…
Recheck dueFree: YesAPI: YesOpen: No
Developer-friendly
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%.
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: 2026-07-27.
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.
Temporary Accounts remove real signup friction and delete unclaimed previews after 60 minutes. The claim URL and temporary token are sensitive values, so production…
The Go Team launched a public GET-only v1beta pkg.go.dev API for structured search and package ecosystem metadata, including packages, modules, symbols, versions, known vulnerabilities and imported-by relationships, with…
Recheck dueFree: YesAPI: YesOpen: Yes
Developer-friendlyGitHub tractionTraction signal
The pkg.go.dev API replaces brittle HTML scraping with an official structured interface and gives AI coding tools a cleaner evidence source. It remains v1beta,…
OpenAI announced an agreement to acquire Ona, subject to customary closing conditions, with the stated intent to bring Ona’s secure, persistent, customer-controlled cloud execution and orchestration technology into…
Recheck dueFree: NoAPI: NoOpen: No
Business-friendlyDeveloper-friendly
Ona gives OpenAI a credible route toward persistent, governed execution for Codex, but the announcement is a transaction and product-direction statement, not proof that…
Google announced that it had joined the Eclipse Foundation as a Strategic Member effective April 2026. Google says it will sponsor Open VSX, use the Open VSX Managed…
Recheck dueFree: NoAPI: NoOpen: No
Developer-friendly
The membership matters less as a brand announcement than as governance and infrastructure support for Open VSX, which is used by multiple AI-integrated developer…
Datadog introduced Pup, an Apache-2.0 agent-oriented CLI with dynamic schemas and structured output across more than 200 commands, alongside a separate MIT-licensed Agent Skills repository.
Recheck dueFree: YesAPI: YesOpen: Yes
Developer-friendlyGitHub tractionTraction signal
Launch readiness
8.0 / 10
Demo evidence
Not scored yet
Creator-story fit
Not scored yet
Score definitions and rubric
These are launch-record readiness heuristics, not product ratings.
Launch readiness
How complete and reviewable the launch record is, not the quality of the product.
Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.
Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.
Demo evidence
Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.
Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.
Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.
Creator-story fit
Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.
Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.
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: 2026-07-27.
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.
Datadog Pup is a practical fit for SRE teams that need structured, terminal-native investigations under a purpose-scoped identity. Its OAuth, inherited RBAC and dynamic…
Mistral AI released Search Toolkit in public preview as an open-source framework for ingestion, retrieval, and evaluation in production AI search pipelines.
Recheck dueFree: YesAPI: NoOpen: Yes
Business-friendlyDeveloper-friendlyGitHub 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%.
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 released Search Toolkit in public preview — an open-source framework bundling ingestion, retrieval, and evaluation for production AI search pipelines, with a public…
OpenAI released GPT-Realtime-2, GPT-Realtime-Translate, and GPT-Realtime-Whisper for realtime voice reasoning, translation, and streaming transcription in the API.
Recheck dueFree: NoAPI: YesOpen: No
Business-friendlyDeveloper-friendlyTraction signal
A high-signal API launch because it moves voice AI toward realtime agents that can reason, translate, transcribe, and act during a conversation.
OpenAI introduced GPT-Rosalind, a purpose-built frontier reasoning model for biology, drug discovery, translational medicine, and scientific workflows.
Recheck dueFree: NoAPI: YesOpen: No
Business-friendlyDeveloper-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%.
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 for life-sciences research on April 16, 2026. Its September 11 update says the model is out of research preview and available…
Mistral AI introduced Forge, an enterprise system for building frontier-grade AI models grounded in proprietary institutional knowledge.
Recheck dueFree: NoAPI: NoOpen: No
Video demoBusiness-friendlyDeveloper-friendlyTraction signal
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%.
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…
Google Cloud announced expanded ways to build and scale AI agents with Vertex AI Agent Builder, reinforcing the platform’s agent development and deployment story.
Recheck dueFree: NoAPI: YesOpen: No
Video demoDeveloper-friendly
A platform-level update that matters for enterprises standardizing agent infrastructure on Google Cloud.
Mistral AI launched an Agents API with built-in connectors for code execution, web search, image generation, MCP tools, memory, and orchestration.
Recheck dueFree: NoAPI: YesOpen: No
Video demoBusiness-friendlyDeveloper-friendlyTraction signal
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…
Anthropic introduced web search on the API so developers can build Claude applications that retrieve and cite current web information.
Recheck dueFree: NoAPI: YesOpen: No
Business-friendlyDeveloper-friendlyTraction 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%.
0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
Assigned by
Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
Rubric and check date
Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-08.
Confidence and missing data
Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
Freshness
Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
Disputes
Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.
Anthropic introduced web search on the Claude API, letting developers build applications that retrieve and cite current web information as a first-party tool, priced…
CircleCI announced its original open-source MCP Server for AI-assisted access to pipeline, workflow, job, log, test and artifact context. CircleCI now marks that standalone server deprecated and directs…
Recheck dueFree: NoAPI: YesOpen: Yes
Developer-friendlyGitHub tractionTraction 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%.
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.
The CircleCI MCP launch established a useful bridge from CI evidence to coding assistants, but the original standalone implementation is no longer the forward…
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 Open-Weight Models
Cloudflare Clef / Clef-flash
Summary: Cloudflare released Clef and Clef-flash, decision models that produce structured choices and probabilities. The family is hosted on Workers AI and distributed as Apache-2.0 weights for…
Why it matters: Clef and Clef-flash give developers hosted and local options for structured decisions. Compare them on your own decision tasks; Cloudflare’s benchmark results are vendor…
Pricing
Hosted inference is subject to Workers AI usage billing; open weights are distributed under Apache 2.0 and local inference requires compute. The announcement does not establish a universal free hosted plan or self-service fine-tuning price.
Summary: The Strands team released Decider 2B, a small decision model that chooses among defined outputs and assigns probabilities. The release includes model weights, code, data and…
Why it matters: Strands Decider 2B fits experiments that need a model to choose among defined options. It is not a general chat or coding model; evaluate…
Pricing
The release offers public code, weights and data for local experimentation. Running or training it requires local or rented compute; no hosted API price or hosted free plan is established by the announcement.
Summary: Earendil released Pi Durable as a new experimental package for long-running agent applications. It extends the Pi ecosystem with durable task and conversation execution rather than…
Why it matters: Pi Durable offers builders a package to explore agents that survive interruptions and run across different surfaces. Keep evaluations scoped to the experimental release…
Pricing
The package is MIT licensed and available through npm. The announcement does not establish a hosted-service subscription or free inference; model and infrastructure usage can incur separate charges.
Summary: Griffin and Griffin-Lite are presented as models for responsive audiovisual interaction in a restricted research preview. Access: Restricted research preview; not customer GA.
Why it matters: Griffin is research access to investigate. A customer deployment or a public price is not established.
Pricing
No separate event-specific price is stated in the reviewed release notice. Existing account, plan, usage or hardware terms may apply; check the official source before committing.
Summary: One API endpoint supports generation, local edits and up to ten reference images. Output reaches 4K with 15 aspect ratios; bounding boxes belong in the prompt.…
Why it matters: FLUX 3 Image offers several composition controls in one endpoint. Check them on your own reference set before replacing a production image workflow.
Pricing
$0.041 at 768sq, $0.048 at 1k, $0.100 at 1.5k and $0.607 at 4k per image in the release note. Resolution controls cost.
Summary: Google DeepMind released research on watermarking AI-generated biological sequences and structures, alongside public code and data. This record covers the research release. Access: Research release only;…
Why it matters: SynthID Bio gives researchers code and data to examine biological watermarking. Review the relevant model-weight terms before reuse; the release does not establish a…
Pricing
No hosted-service plan is established. Repository software uses Apache 2.0 and publication data uses CC-BY. ProteinMPNN parameters retain MIT terms; AlphaFold 3 parameters have separate terms. Research use is distinct from clinical use.
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.
OpenAI reusable prompt objects and v1/prompts are scheduled to shut down November 30, 2026
Summary: OpenAI announced reusable-prompt deprecation on June 3, 2026. The documented November 30 shutdown covers reusable prompt objects and v1/prompts. Move managed prompt content into application-owned code…
Why it matters: Treat saved OpenAI prompt objects as a migration dependency before November 30. Move their content and variables into application code, then validate the generated…
Three GPT Image API models are scheduled to retire December 1, 2026
Summary: OpenAI schedules gpt-image-1-mini, gpt-image-1.5 and chatgpt-image-latest for API removal on December 1, 2026. Its current deprecation table recommends gpt-image-2.5-sunburst or gpt-image-2.5-flare.
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 current deprecation table recommends gpt-image-2.5-sunburst or gpt-image-2.5-flare. 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.
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Fridays at 09:00 Vancouver time: source-checked AI changes, original tests and one practical thing to try. We skip a week when there is not enough verified material. Free. Unsubscribe anytime.
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.
Fridays at 09:00 Vancouver time: source-checked AI changes, original tests and one practical thing to try. We skip a week when there is not enough verified material. Free. Unsubscribe anytime.
ModelsAgents & harnessesDeveloper infrastructureProductsFunding & company movesPricing watchUnder the radar