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…
Liquid AI released the base and post-trained LFM2.5-2.6B checkpoints on August 4, 2026. The post-trained text model targets agentic workloads and ships in native, GGUF, MLX, and ONNX…
Recheck dueFree: UnknownAPI: UnknownOpen: Yes
Creator coverageStrong demoClear use caseVideo demo
Launch readiness
9.2 / 10
Demo evidence
7.5 / 10
Creator-story fit
Medium
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: 2026-08-07.
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.
LFM2.5-2.6B is a credible option for high-volume, privacy-sensitive local agents where compact size and tool use matter more than frontier reasoning. Treat it as…
DeepSeek released DeepSeek-V4-Flash-0731 as the official V4-Flash API public beta. The checkpoint keeps the preview model’s architecture and size but adds new post-training, native Responses API support, and…
Recheck dueFree: NoAPI: YesOpen: Yes
Clear use caseVideo demoDeveloper-friendlyTraction signal
Worth testing for cost-sensitive coding-agent workloads because it combines native Codex support, a one-million-token context window, very low API pricing and MIT-licensed weights. Treat…
GitHub made its Copilot cloud agent integration for Linear generally available, allowing teams to assign Linear issues to an asynchronous coding agent.
Recheck dueFree: NoAPI: UnknownOpen: Unknown
Clear use caseDeveloper-friendly
Copilot cloud agent for Linear addresses a concrete need: The integration moves agent assignment into an issue tracker that many software teams already use,…
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…
Recheck dueFree: NoAPI: NoOpen: Unknown
Clear use caseBusiness-friendly
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…
The open plugin connects Hermes to Humalike’s behavioral APIs. It can decide when the agent should join a conversation, rewrite replies to match a group’s style, build a…
Recheck dueFree: YesAPI: YesOpen: Yes
Clear use caseBeginner-friendlyCreator-friendlyDeveloper-friendly
Humalike x Hermes addresses a concrete need: Agent quality in group settings depends on timing, restraint, and social context as well as answer quality.…
Rex launched a set of governed AI agents for collections, customer-portal work, accounts-receivable inboxes, cash application, and dispute handling.
Recheck dueFree: NoAPI: UnknownOpen: Unknown
Clear use caseBusiness-friendly
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…
Creed launched a portable Markdown-based context file that gives supported AI agents a user-controlled record of preferences, projects, and working style.
Recheck dueFree: YesAPI: UnknownOpen: Yes
Clear use caseBeginner-friendlyBusiness-friendlyDeveloper-friendly
Creed addresses a concrete need: Users increasingly move among several assistants, while the context each one learns usually stays trapped in a product. The…
Deck launched an AI chief of staff with its own inbox, letting a user copy selected email threads, assign follow-up work, and schedule recurring routines without granting full…
Recheck dueFree: YesAPI: UnknownOpen: Unknown
Clear use caseBeginner-friendlyBusiness-friendly
Deck addresses a concrete need: Giving an assistant its own inbox offers a narrower permission model than granting access to an entire mailbox, while…
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.
Recheck dueFree: UnknownAPI: YesOpen: Unknown
Clear use caseBusiness-friendly
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:…
Fuzzy AI launched a relationship-first sales workspace that combines prospect research, LinkedIn engagement, personalized outreach, sequencing, and human-reviewed replies.
Recheck dueFree: NoAPI: UnknownOpen: Unknown
Clear use caseBeginner-friendlyBusiness-friendly
Fuzzy AI addresses a concrete need: Fuzzy reflects a shift from high-volume AI prospecting toward systems that try to coordinate research, public engagement, and…
Skippr AI launched an embeddable real-time agent that can speak with users, understand an application's context, demonstrate workflows, and operate the product with approval controls.
Recheck dueFree: NoAPI: YesOpen: Unknown
Clear use caseBusiness-friendlyDeveloper-friendly
Skippr AI addresses a concrete need: Skippr represents a product-interface trend in which software companies embed an agent that can demonstrate and operate the…
OpenClaw v2026.7.1 shipped major Control UI and onboarding overhauls, major updates to the official iOS, Android, and macOS apps, expanded model and provider support, and stronger Codex and…
Recheck dueFree: UnknownAPI: UnknownOpen: Unknown
Clear use caseGitHub tractionTraction signal
OpenClaw v2026.7.1 is a substantive platform release rather than a narrow patch: the interface, onboarding, companion apps, and provider and coding-agent paths move together.…
In the latest iOS and Android production builds, GitHub Mobile can prefill a pull-request comment asking Copilot cloud agent to resolve merge conflicts; the user reviews and submits…
Recheck dueFree: NoAPI: NoOpen: No
Clear use caseDeveloper-friendly
The mobile shortcut is useful for starting work, not for proving that a conflict was resolved correctly. GitHub prepopulates a request from the pull-request…
GitHub summarized Copilot changes across Visual Studio Code 1.123 through 1.127, including integrated browser interaction, parallel agent sessions, chat organization, AI-credit visibility, model-provider discovery and Autopilot behavior.
Recheck dueFree: YesAPI: NoOpen: No
Clear use caseDeveloper-friendly
The June roundup shows VS Code becoming an orchestration surface for multiple agents, browser checks and model choices rather than a single coding chat.…
GitHub added Codex as an optional public-preview agent provider in GitHub Copilot for JetBrains IDEs and shipped related agentic enhancements including hooks support, richer MCP server management and…
Recheck dueFree: NoAPI: NoOpen: No
Clear use caseDeveloper-friendly
Provider choice inside JetBrains can reduce tool switching, but Codex, Claude and Copilot modes should not be treated as equivalent harnesses. The release is…
Katalyst appeared on Product Hunt on July 7, 2026 with positioning around an AI agent for Salesforce pipeline work, including AI Resolution, meeting recorder, hygiene scores, and deal…
Recheck dueFree: UnknownAPI: UnknownOpen: Unknown
Product Hunt tractionClear use caseVideo demoTraction signal
Launch readiness
6.1 / 10
Demo evidence
Not scored yet
Creator-story fit
Not scored yet
Score definitions and rubric
These are launch-record readiness heuristics, not product ratings.
Launch readiness
How complete and reviewable the launch record is, not the quality of the product.
Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.
Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.
Demo evidence
Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.
Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.
Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.
Creator-story fit
Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.
Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.
0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
Assigned by
Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
Rubric and check date
Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-07-08.
Confidence and missing data
Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
Freshness
Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
Disputes
Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.
Katalyst launched on Product Hunt with an AI agent for Salesforce pipeline work — AI Resolution, a meeting recorder, hygiene scores, and deal patterns…
Google introduced the Genkit Agents API in preview for TypeScript and Go, with a shared chat interface, streaming, server- or client-managed state, snapshots, human interrupts, detached tasks and…
Recheck 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.
Genkit Agents API removes repeated full-stack agent plumbing while leaving teams in control of runtime and state ownership. The preview can introduce breaking changes…
GitHub Copilot for Jira reached general availability, adding real-time Copilot cloud-agent progress inside Jira, post-session steering and simplified onboarding for connected GitHub repositories.
Recheck dueFree: NoAPI: UnknownOpen: No
Clear use caseBusiness-friendlyDeveloper-friendly
The GA release closes useful workflow gaps by returning agent progress and follow-up control to Jira. The integration also moves ticket context into a…
No source-ready records are tagged for today yet, so this section is showing the latest public launch records available in the tracker.
AI Models
GPT-6 Sol
Summary: OpenAI added GPT-6 Sol to the API as gpt-6-sol and began rolling it out in ChatGPT Work and Codex to eligible paid plans on September 22,…
Why it matters: GPT-6 Sol merits a workload-specific trial when Astra costs more than the task warrants. Kingy's September 22 comparison finds lower cost per task on…
Pricing
OpenAI lists standard direct API rates of US$2 per million input tokens and US$10 per million output tokens for requests with at most 272K input tokens, checked September 22, 2026. Longer context, caching and processing tiers have different rates; consult the official model pricing.
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.
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.
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.
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.
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.
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.
Three GPT Image API models are scheduled to retire December 1, 2026
Summary: OpenAI announced an API lifecycle deadline for gpt-image-1-mini, gpt-image-1.5 and chatgpt-image-latest. Those model IDs are scheduled to shut down on December 1, 2026, with gpt-image-2 listed…
Why it matters: OpenAI schedules gpt-image-1-mini, gpt-image-1.5 and chatgpt-image-latest for API removal on December 1, 2026. Its deprecation table names gpt-image-2 as the replacement. Inventory the three…
Pricing
Review the current price of the chosen replacement and measure representative jobs. This lifecycle record does not establish workload cost or promise a cost-neutral migration.
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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.
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