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
2+
Top builder-critical changes
What could break your stack this week
- highNVIDIA-Nemotron-3.5-Transcribe-30B-A4B momentum +30%nvidia
- highDeepSeek-V4.1-Flash-1017 momentum +30%deepseek-ai
- highNanbeige4.3-33B momentum +30%Nanbeige
- highLFM3-1.7B momentum +30%LiquidAI
- highflint momentum +30%RecursiveSI
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
Thin, Light and Built for Everything: NVIDIA RTX Spark Windows Laptops Gain New Models, Agent Tools and Games
Meta
Reimagining Independence: How Meta’s AI Models Are Helping the University of Pittsburgh Transform Assistive Robotics
Our newest AI Quest: Mapping the human brain
Microsoft
Local know-how helps communities make the most of new technology and opportunities
OpenAI
From model to agent: Equipping the Responses API with a computer environment
Anthropic
Claude 3.5, Constitutional AI
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.
DeepSeek-V4.1-Flash-1017 momentum +30%
deepseek-ai • DeepSeek-V4.1-Flash-1017
Nanbeige4.3-33B momentum +30%
Nanbeige • Nanbeige4.3-33B
LFM3-1.7B momentum +30%
LiquidAI • LFM3-1.7B
flint momentum +30%
RecursiveSI • flint
xAI raised $6B (Series C)
Funding Radar • xAI
AI & robotics reshape Australian trades, says expert
Channellife Australia • AI News
Anthony Joseph Amaradio Explains How Technology Enhances Money Management
Financialcontent • 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
Meta
Apple
NVIDIA
Amazon
Market data delayed. For informational purposes only.
Latest Research
View allElucidating the Design Space of LM Data Attribution
Data attribution methods for Language Models (LMs) are typically evaluated using downstream tasks like fact retrieval. However, existing evaluations vary multiple dataset properties simultaneously, making it impossible to isolate exactly why an attribution algorithm fails. To diagnose these failures...
arXivPropose-Filter-Release: Scaling Noise to Typical Sensitivity via Private Filtering
An estimator can be accurate and stable on typical data, yet sensitive to a few possible records. Differentially private mechanisms commonly scale their noise to the worst-case influence of a single record, which lets these records dictate the noise even when the remaining data would allow far less....