Track what happened after the launch announcement: browse the source-linked AI feature availability tracker, including plan, region and platform scope. Kingy has not tested account-level access.
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.
kausable raises €12 million for adaptive causal AI
Heidelberg-based kausable raised a verified €12 million seed round to develop causal AI models intended to adapt to new contexts with minimal data.
kausable seed round addresses a concrete need: The funding backs a technically different approach to adaptive AI, but claims about eliminating retraining and handling…
Kastra runtime authorization for AI agents
Kastra applies policies to tools, prompts, inputs, and outputs across several agent environments. Its product pages describe local enforcement, centralized policy management, audit trails, and integrations spanning coding…
Kastra addresses a concrete need: As agents gain access to files, credentials, and operational systems, authorization must happen at action time. The main limitation…
OpenAI Presence managed enterprise agents
Each deployment begins with a defined job and limited access to the knowledge and systems required for that job. Companies set policies, approved actions, and escalation conditions. Simulations…
OpenAI Presence addresses a concrete need: The launch packages agent design, deployment controls, operational evaluation, and post-launch improvement into one managed enterprise offering rather…
Rex governed agents for order-to-cash work
Rex launched a set of governed AI agents for collections, customer-portal work, accounts-receivable inboxes, cash application, and dispute handling.
Rex addresses a concrete need: Order-to-cash work crosses inboxes, finance systems, and customer portals, making it a useful test of whether agentic software can…
Lunen enterprise agent orchestration layer
Lunen.ai launched an early-access enterprise orchestration layer for defining agents in plain language and governing their tools, data access, approvals, schedules, and audit trails.
Lunen.ai addresses a concrete need: Enterprises experimenting with agents need controls at the action layer, not only prompt guidelines. The main limitation is this:…
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…
- 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…
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.
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…
strictKnownMarketplaces for Copilot CLI and VS Code
GitHub launched public-preview strictKnownMarketplaces support in enterprise-managed settings for Copilot CLI and Visual Studio Code, restricting plugin installation to explicitly configured marketplace sources.
strictKnownMarketplaces for Copilot CLI and VS Code provides a useful fail-closed plugin-source boundary, including complete lockdown with an empty list. The public preview does…
GitHub Copilot AI Credits Usage Metrics API
GitHub added the ai_credits_used field to enterprise and organization Copilot usage-metrics API reports, exposing an overall per-user total in the one-day and 28-day user endpoints.
Per-user AI-credit totals give administrators a practical way to spot consumption concentration and build internal reporting. The field is deliberately coarse: GitHub says it…
ChatGPT Enterprise Usage Analytics and Spend Controls
OpenAI introduced expanded ChatGPT Enterprise credit analytics and spend controls, including user, product and model breakdowns, a unified Cost API, workspace defaults, group limits, user overrides and increase…
The release gives enterprise administrators a more useful operating loop: observe usage, set layered limits, review exceptions and reconcile against billing. It does not…
G+D opens Montréal AI Hub for security-critical systems
Giesecke+Devrient announced the opening of its AI Hub in Montréal, physically embedded at Mila and positioned as the centre of the company’s global AI capability. G+D says the…
The hub is strategically credible because it connects G+D’s existing security domains with Montréal’s research ecosystem and a named Mila location. The useful evidence…
CrowdStrike Continuous Identity for AI Agents
CrowdStrike announced Continuous Identity for AI Agents, a Falcon Next-Gen Identity Security capability intended to give agents verifiable workload identities and authorize each action using owner, caller, device-risk…
CrowdStrike’s continuous-authorization model addresses a real weakness in long-lived agent credentials, and the announcement is unusually specific about owner, caller, device and delegation context.…
OpenAI Partner Network
OpenAI launched a global program for firms that build, sell and deliver AI solutions, with Select, Advanced and Elite tiers, a public partner directory, planned specializations and a…
The Partner Network gives enterprises a more structured way to discover OpenAI-focused delivery firms and gives partners clearer tiers and program infrastructure. A directory…
Evaluation Cards
The EvalEval Coalition beta-launched Evaluation Cards, an open-source reader over a normalized evaluation warehouse with card-level context and four interpretive signals: reproducibility, completeness, provenance and comparability.
Evaluation Cards is a useful antidote to treating benchmark scores as self-explanatory because it foregrounds reporting gaps and provenance. Its signals still depend on…
OpenAI Ona Acquisition for Codex
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…
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…
CoSupport AI 2.0 adds decision logs and action-capable support workflows
CoSupport says version 2.0 replaces its earlier single-pass retrieval flow with multi-step search and validation. The update adds per-reply decision logs, an Agentic API for actions in connected…
Watch. CoSupport AI 2.0 is a substantive operations-focused update, particularly for teams that need decision visibility and actions through Shopify or Stripe. Its performance,…
Vibe gets to work.
Mistral AI relaunched Le Chat as Vibe, a unified agent for long-horizon work and coding with Work Mode, Code Mode, VS Code support, CLI updates, and mobile access.
- Launch readiness
- 7.1 / 10
- Demo evidence
- Not scored yet
- Creator-story fit
- Not scored yet
Score definitions and rubric
These are launch-record readiness heuristics, not product ratings.
Launch readiness
How complete and reviewable the launch record is, not the quality of the product.
Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.
Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.
Demo evidence
Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.
Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.
Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.
Creator-story fit
Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.
Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.
Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.
- Scale
- 0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
- Assigned by
- Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
- Rubric and check date
- Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-08.
- Confidence and missing data
- Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
- Freshness
- Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
- Disputes
- Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.
Mistral relaunched Le Chat as Vibe, a unified agent for long-horizon work and coding with Work Mode, Code Mode, VS Code support, CLI updates,…
Introducing Search Toolkit
Mistral AI released Search Toolkit in public preview as an open-source framework for ingestion, retrieval, and evaluation in production AI search pipelines.
- Launch readiness
- 7.1 / 10
- Demo evidence
- Not scored yet
- Creator-story fit
- Not scored yet
Score definitions and rubric
These are launch-record readiness heuristics, not product ratings.
Launch readiness
How complete and reviewable the launch record is, not the quality of the product.
Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.
Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.
Demo evidence
Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.
Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.
Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.
Creator-story fit
Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.
Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.
Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.
- Scale
- 0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
- Assigned by
- Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
- Rubric and check date
- Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-08.
- Confidence and missing data
- Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
- Freshness
- Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
- Disputes
- Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.
Mistral released Search Toolkit in public preview — an open-source framework bundling ingestion, retrieval, and evaluation for production AI search pipelines, with a public…
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.
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.
- Verification
- Source-verified; 1 source
Strands Decider 2B
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.
- Verification
- Source-verified; 3 sources
Pi Durable
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.
- Verification
- Source-verified; 3 sources
Tavus Griffin / Griffin-Lite
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.
- Verification
- Source-verified; 2 sources
FLUX 3 Image
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.
- Verification
- Source-verified; 2 sources
SynthID Bio
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.
- 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
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…
- Pricing
- Pricing unknown
- Verification
- Source-verified; 5 sources
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.
- Verification
- Source-verified; 5 sources
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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
The Kingy AI Referral Index
AI assistants sent 1.3279% of kingy.ai's own traffic. Published studies put the web-wide figure anywhere from under 1% to 25%. The index reconciles them, catalogued by method.
Methodology
How Kingy AI Scores Launches
Kingy AI scoring is designed for launch discovery, editorial review, creator planning, and buyer trust checks.
Kingy score
A directional editorial score for launch clarity, source quality, audience fit, pricing visibility, demo usefulness, and practical buyer or creator value.
Demo score
A signal for whether the product can be shown, tested, explained, or compared without relying on vague announcement copy.
YouTube potential
A creator-fit signal for demos, tutorials, before-and-after workflows, explainers, reviews, and audience-specific product education.
Source verification
Records distinguish verified, needs verification, and founder submitted status using official URLs, source links, last-verified dates, and correction paths.
Pricing clarity
Pricing signals favor launches with visible pricing, free-plan status, pricing pages, API access notes, or clear uncertainty when pricing is not public.
Use-case clarity
Launches are easier to evaluate when the audience, workflow, category, demo, and alternative comparison are obvious from public sources.
Founder and sponsor fit
Founder submissions and sponsor interest are routing signals only; editorial review still checks source quality, public claims, demo clarity, and usefulness.
Verification labels
Verified means enough public source evidence is present, needs verification means the record needs more checking, and founder submitted means the entry came through the submission path.
Scores are editorial signals, not scientific benchmarks, paid placements, or guarantees.
Founder submission
Submit Your AI Launch
Founders can send a launch for editorial review when the public source trail is ready to verify.
What to include
- Product name
- Website
- Launch date
- What launched
- Official source links
- Pricing page
- Demo/video
- Company info
- Category
- Public funding info
- Screenshots/media
Privacy note
Do not submit secrets, unreleased financials, private customer data, or regulated personal data.
Submit only public product, company, source, pricing, demo, and media details that Kingy AI can review without logging into private systems.
Sponsor path
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