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.
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…
Source-verifiedFree: 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…
Rex launched a set of governed AI agents for collections, customer-portal work, accounts-receivable inboxes, cash application, and dispute handling.
Source-verifiedFree: 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.
Source-verifiedFree: 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…
Source-verifiedFree: 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.
Source-verifiedFree: 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.
Source-verifiedFree: 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.
Source-verifiedFree: 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…
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.
Source-verifiedFree: 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…
Genspark announced a $100 million Series B extension that it says brought the round to $485 million at a $2.6 billion post-money valuation, alongside a chief revenue officer…
Source-verifiedFree: YesAPI: NoOpen: No
Clear use caseVideo demoBeginner-friendlyBusiness-friendly
The extension increases Genspark’s stated capacity to pursue enterprise distribution, but capital raised is not product validation. The funding, valuation, ARR, investor, model-count and…
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…
Source-verifiedFree: NoAPI: NoOpen: No
Clear use caseBusiness-friendly
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 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…
Source-verifiedFree: NoAPI: NoOpen: No
Clear use caseBeginner-friendlyBusiness-friendly
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…
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…
Source-verifiedFree: NoAPI: NoOpen: No
Clear use caseBusiness-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…
Replit introduced SEO Agent, which scans published apps, identifies discoverability issues, and can apply fixes for web search and AI search visibility.
Recheck dueFree: YesAPI: NoOpen: No
Clear use caseVideo demoBeginner-friendlyBusiness-friendly
Launch readiness
6.4 / 10
Demo evidence
Not scored yet
Creator-story fit
Not scored yet
Score definitions and rubric
These are launch-record readiness heuristics, not product ratings.
Launch readiness
How complete and reviewable the launch record is, not the quality of the product.
Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.
Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.
Demo evidence
Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.
Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.
Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.
Creator-story fit
Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.
Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.
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.
Replit introduced SEO Agent, which scans published apps, flags discoverability issues, and can apply fixes for web and AI search visibility (replit.com). Replit Builders…
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…
UnknownFree: NoAPI: YesOpen: No
Product Hunt tractionClear use caseVideo demoBusiness-friendly
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,…
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.
Recheck dueFree: YesAPI: YesOpen: No
Clear use caseVideo demoBusiness-friendlyDeveloper-friendly
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%.
Anthropic released Claude Opus 4.8 with improved coding, agentic task performance, professional work quality, effort controls, and Claude Code dynamic workflows.
Recheck dueFree: NoAPI: YesOpen: No
Clear use caseVideo demoBusiness-friendlyDeveloper-friendly
Launch readiness
7.9 / 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%.
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 released Claude Opus 4.8 with improved coding, agentic task performance, effort controls, and Claude Code dynamic workflows, priced at $5 per million input…
Cohere released Command A+ as an Apache 2.0 open-source MoE model optimized for reasoning, multilingual, multimodal, RAG, and agentic workflows.
Recheck dueFree: YesAPI: YesOpen: Yes
Clear use caseBusiness-friendlyDeveloper-friendlyTraction signal
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%.
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,…
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
Clear use caseBusiness-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.
No source-ready records are tagged for today yet, so this section is showing the latest public launch records available in the tracker.
AI Voice/Audio Tools
gamedai live AI sports radio
Summary: gamedai says its live AI sports-radio service went live on August 7, 2026 for the NFL preseason. The launch page describes coverage for all 16 Week…
Why it matters: gamedai is an interesting vertical-agent launch because it joins live data, retrieval, voice generation, and an evaluation layer around one narrow listener job. The…
Pricing
The official homepage lists a free Casual tier, Premium at $9.99 per month with a seven-day free trial, and a $99.99 one-time Lifetime unlock. The reviewed Join Now link returned a deployment-not-found page, so signup and billing availability were not independently confirmed.
Summary: 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,…
Why it matters: 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…
Pricing
The model weights are downloadable under Liquid AI's LFM1.0 license. Liquid AI did not announce a paid hosted API price for this release, and the reviewed Hugging Face page says no inference provider currently deploys the model. Self-hosting avoids a vendor per-token fee but still carries hardware, electricity, engineering, and support costs.
DeepSeek V4-Flash-0731 launches in API beta with native Codex support
Summary: 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…
Why it matters: 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…
Pricing
$0.0028 per 1M cached input tokens; $0.14 per 1M uncached input tokens; $0.28 per 1M output tokens. DeepSeek says future peak-hour prices will be 2× regular rates, with no effective date announced.
OpenAI releases Codex Security CLI and TypeScript SDK in limited beta
Summary: OpenAI published the Codex Security command-line client and TypeScript SDK. The CLI supports repository and change review, bulk scans, history, CI workflows, SARIF output and false-positive…
Why it matters: The CLI and SDK make Codex Security easier to insert into repeatable engineering workflows and expose useful integration primitives such as typed findings, SARIF,…
Pricing
OpenAI does not publish self-serve Codex Security pricing in the reviewed documentation. CLI and SDK access is limited to approved beta customers and partners through an OpenAI account team. Commercial terms, quotas and any Trusted Access for Cyber requirement are account-specific.
Model Context Protocol 2026-07-28 specification goes final
Summary: The final Model Context Protocol 2026-07-28 specification became the current authoritative protocol version. It replaces connection-level state with self-contained requests, moves capability negotiation to each request…
Why it matters: The 2026-07-28 MCP specification makes a consequential architectural trade: stateless, self-contained requests can simplify scaling and recovery, but implementations must now negotiate and validate…
Pricing
MCP is an open protocol specification, not a paid hosted product. Implementations, infrastructure, models, connectors and support can carry separate costs. The official specification and governance pages are the authority for the protocol boundary.
Summary: Microsoft announced Project Perception, an agentic security system that coordinates specialized red, blue, and green agents inside Microsoft Defender.
Why it matters: The launch brings attack simulation, defense testing, and threat-scenario planning into one Microsoft Defender workflow. Its practical effectiveness and cost remain unproven until security…
Pricing
Microsoft says Project Perception uses consumption-based, pay-as-you-go pricing measured in Security Compute Units (SCUs). Different agents consume SCUs at different rates; Microsoft did not publish numeric SCU rates in the checked launch sources.
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 Developer Tools
Google Imagen 4 API shutdown window: August 17, 2026
Summary: Google announced that imagen-4.0-generate-001, imagen-4.0-ultra-generate-001 and imagen-4.0-fast-generate-001 are deprecated. Its deprecations table lists August 17, 2026 as the earliest possible shutdown date and recommends gemini-3.1-flash-image.
Why it matters: Plan against August 17 while preserving Google’s wording: the deprecations page says listed dates are the earliest possible shutdown dates and that exact timing…
Pricing
There is no separate migration fee. Replacement Gemini API image generation follows current Google pricing and quota terms; teams should compare the selected model, image output, prompts and workload mix on the live pricing page.
OpenAI Assistants API migration deadline: August 26, 2026
Summary: OpenAI’s Assistants API reaches its shutdown deadline on August 26, 2026. OpenAI recommends Responses API and Conversations API, with documented mappings from Assistants to configuration or…
Why it matters: Treat August 26 as an operational deadline, not a feature launch or a find-and-replace exercise. OpenAI documents object and orchestration changes, including explicit tool-loop…
Pricing
There is no separate migration fee. Replacement API usage is billed under current OpenAI API pricing, while engineering, regression testing, data migration, observability and rollback work remain implementation costs.
Google retires Gemini Robotics ER 1.6 Preview on August 31
Summary: Google announced that gemini-robotics-er-1.6-preview will shut down on August 31, 2026, and its deprecation table names gemini-robotics-er-2-preview as the replacement.
Why it matters: Google announced that gemini-robotics-er-1.6-preview will shut down on August 31, 2026, and its deprecation table names gemini-robotics-er-2-preview as the replacement. Kingy’s action: Replace the…
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.