Track the market, not tabs
Watch competitors, launches, pricing, product changes, and GitHub activity from one evidence-backed timeline.
Company intelligence for AI teams
Know what your AI market will do next.
AIIStack turns fragmented public signals into source-backed company intelligence: competitor moves, AI visibility, market momentum, and the next action worth taking.
Evidence on every material changeScores with methodologyNo paid ranking
Measure AI answer visibility
See whether your company is recommended or cited across a documented panel of buyer-intent prompts.
Act before the next meeting
Get only material changes, with a source, confidence score, and a weekly report your team can use.
Source-backed activity
What changed across AI companies
Every event has a source, a capture date, and a confidence level. The profile is the public graph; your workspace turns it into a decision system.
Mention spike
Notable
25 new attributable Hacker News discussions were observed in the last seven days.
Mention spike
Notable
25 new attributable Hacker News discussions were observed in the last seven days.
Mention spike
Notable
25 new attributable Hacker News discussions were observed in the last seven days.
Mention spike
Monitor
4 new attributable Hacker News discussions were observed in the last seven days.
Mention spike
Monitor
3 new attributable Hacker News discussions were observed in the last seven days.
Company graph
Companies with momentum worth understanding
cursor.com
An AI-native code editor that pairs a familiar IDE with model-assisted editing, refactoring, and codebase-aware chat.
- Coverage
- Building
comet.com
An ML and LLM evaluation company whose open-source Opik tool traces, evaluates, and monitors LLM applications.
- Coverage
- Building
traceloop.com
An LLM reliability platform built on OpenLLMetry, an open-source OpenTelemetry-based observability standard.
- Coverage
- Building
Market maps
Follow the categories that matter to you
Agent frameworks
2Frameworks and platforms for building, orchestrating, and deploying AI agents and knowledge-grounded applications.
AI coding assistants
0Developer tools that generate, review, refactor, and maintain software alongside engineering teams — IDE assistants, agents, and code-review copilots.
AI inference platforms
3Cloud platforms that run, optimize, fine-tune, or serve AI models for developers and production applications.
AI & MLOps
1Tools for training, evaluating, observing, and operating machine-learning and AI systems.
AI observability & evaluation
0Tracing, evaluation, monitoring, and reliability systems for teams shipping LLM and agent applications to production.
Foundation models
4Companies building and serving general-purpose AI models through research, APIs, and enterprise platforms.
Model development platforms
1Platforms for discovering, sharing, building, and operating machine-learning and AI models.
Vector databases
3Data infrastructure for semantic retrieval, hybrid search, and production AI application memory.
Voice AI
1AI platforms for speech synthesis, conversational voice agents, and audio generation.
Methodology & trust
Answers before the claims
AIIStack is designed to make the evidence boundary visible: what is sourced, what is scored, and what is still unknown.
Read the full methodologyIs AIIStack ranking paid or sponsored?
No. Companies cannot pay to change a public score, leaderboard position, market placement, or comparison result. Paid plans cover workspace capabilities, not editorial treatment or ranking.
What does “source-backed” mean on AIIStack?
Material company changes are tied to attributable evidence, a capture date, and a confidence level. When evidence is incomplete, AIIStack shows the gap instead of filling it with an unsupported claim.
How does AIIStack calculate company scores?
Scores normalize documented signals within a relevant cohort and use a versioned model. Each score is shown with confidence and coverage context; it is an intelligence indicator, not an absolute verdict on company quality.
What is AI visibility tracking?
AI visibility measures whether a company appears in answers to a documented panel of buyer-intent prompts. It describes a specific model panel and time period—not a company’s global rank across every AI answer engine.