Ship AI changes with proof, not vibes
A2ZAI Checks runs evals on your repo: a PR scorecard plus a public benchmark card you can drop in READMEs and launch posts. Same site: builder radar for model launches, API shifts, pricing, and outages—so you know when to re-run.
Builder signals
5
Funding tracked
30
Models watched
5
Agents spotted
0+
Top builder-critical changes
What could break your stack this week
- highgemma-4-31B-it momentum +1%Google
- highgemma-4-26B-A4B-it momentum +1%Google
- highgemma-4-E4B-it momentum +1%Google
- highGemma-4-31B-JANG_4M-CRACK momentum +17%dealignai
- highGLM-5.1 momentum +30%zai-org
Sourced from the same live signal pipeline as River. Pin your evals with Checks.
Is your AI stack at risk?
Pick your providers, see critical changes in 10 seconds. Free, no signup, shareable.
Score my prompt
Compare two models on your prompt and get a shareable benchmark URL.
Live River
Quick bytes on launches, deprecations, pricing moves, benchmarks, and breakage risk.
A2ZAI Checks
GitHub-native evals that turn prompt and agent changes into PR scorecards.
Builder Stack
Discover agents today, with MCPs, plugins, SDKs, and technical products rolling in next.
Capital Radar
Funding rounds, acquisitions, and investor moves with builder-first context.
Best places to start
Choose an artifact, not a browse path
The strongest A2ZAI surfaces now end in a public object you can use, share, or route teammates into.
Utility artifact
Run Checks and publish a benchmark card
Best for shipping teams who want a PR scorecard, public benchmark artifact, and shareable proof of improvement.
Open ChecksSignal artifact
Open the live river and jump into quick bytes
Best for scanning launches, deprecations, pricing shifts, and benchmark moves, then opening the strongest byte pages.
Open Live RiverDestination artifact
Use company pages as operating dashboards
Best for sending someone one link that combines official posts, live intel, quick bytes, and capital context.
Explore company pagesCompany Spotlight
NVIDIA
From RTX to Spark: NVIDIA Accelerates Gemma 4 for Local Agentic AI
Meta
Scaling How We Build and Test Our Most Advanced AI
New ways to balance cost and reliability in the Gemini API
Microsoft
Microsoft and Publicis Groupe expand partnership to power the future of agentic marketing
OpenAI
From model to agent: Equipping the Responses API with a computer environment
Anthropic
Anthropic expands partnership with Google and Broadcom for multiple gigawatts of next-generation compute
What changed for builders
Use this stream to spot the change, then move into a stronger destination page: river for the wider feed, company pages for operator context, and Checks for a public benchmark artifact.
gemma-4-31B-it momentum +1%
google • gemma-4-31B-it
Elastic Adhesives Market Trends 2026: Flexible Bonding Solutions Growth
Express-press-release • AI News
Gemma-4-31B-JANG_4M-CRACK momentum +17%
dealignai • Gemma-4-31B-JANG_4M-CRACK
GLM-5.1 momentum +30%
zai-org • GLM-5.1
void-model momentum +30%
netflix • void-model
xAI raised $6B (Series C)
Funding Radar • xAI
Spotify updates prompted playlists for the podcast era
Betanews • AI News
Databricks raised $10B (Series J)
Funding Radar • Databricks
A2ZAI Checks
Catch prompt and agent regressions before merge, then turn the result into a shareable benchmark card.
Explore ChecksBuilder Brief
Get the launches, benchmarks, pricing moves, and outages that matter before your app breaks.
Get AI intelligence briefs
Receive high-signal updates on companies, funding, and models.
Or stay in the loop on X
Follow @_MomentumTraderFunding Radar
View allxAI
$6BSeries C • Foundation Models
Databricks
$10BSeries J • AI Infrastructure
Perplexity
$500MSeries B • AI Applications
Physical Intelligence
$400MSeries A • Robotics
Chosen builder wedge
A2ZAI Checks is the utility layer on top of builder radar
The site stays useful as launch radar and discovery, but the product edge is a shareable scorecard builders can produce every time they ship. Supporting surfaces like learn still exist with 15 lessons and 126+ terms, but they are now secondary to shipping workflows.
Viral Artifact
GitHub PR scorecard
A2ZAI Checks
Prompt regression check for `support-agent.yaml`
Quality
+8.4%
Latency
+220ms
Cost
-31%
Passing: `refund-policy`, `invoice-lookup`, `cancel-subscription`
Regressed: `edge-case-promotions` on `gpt-4.1-mini`
Recommendation: merge after fixing one retrieval prompt and rerunning the pack.
Public Card
Benchmark card
Repo benchmark
support-agent / checkout-recovery
Best model route
Claude Sonnet + GPT-4.1-mini fallback
Win summary
12% better success at 29% lower cost
This is the artifact that spreads on X, GitHub, and founder launches: a benchmark card builders can link to when they ship.
AI Stock Pulse
NVIDIA
Amazon
Microsoft
Meta
Market data delayed. For informational purposes only.
Latest Research
View allPaper Circle: An Open-source Multi-agent Research Discovery and Analysis Framework
The rapid growth of scientific literature has made it increasingly difficult for researchers to efficiently discover, evaluate, and synthesize relevant work. Recent advances in multi-agent large language models (LLMs) have demonstrated strong potential for understanding user intent and are being tra...
arXivIn-Place Test-Time Training
The static ``train then deploy" paradigm fundamentally limits Large Language Models (LLMs) from dynamically adapting their weights in response to continuous streams of new information inherent in real-world tasks. Test-Time Training (TTT) offers a compelling alternative by updating a subset of model...