SHUR IQ | AI Agent Intelligence | W12-2026
YC Ecosystem • 677 Agents Classified
677
SHUR IQ AI Agent Intelligence — W12-2026
YC Ecosystem Classification

677 True AI Agents from 1,672 AI Companies

SHUR IQ classified the entire YC AI portfolio to isolate companies building autonomous agents—not wrappers, not chatbots, not fine-tuning services. The top 10 scored across five structural dimensions reveal where real autonomy is emerging and where capital is chasing vaporware.

W12-2026  |  March 2026  |  First week of scoring — no weekly deltas yet
1,672
AI Companies Scanned
677
True Agent Companies
69.0
Top Composite Score
40.5%
Agent Classification Rate

The Classification Problem

Everyone calls themselves an "AI agent" company in 2026. Of 1,672 AI companies in the YC ecosystem, only 677 (40.5%) meet the structural criteria for agent classification: autonomous task execution, multi-step reasoning, tool integration, and persistent state. The remaining 995 are wrappers, fine-tuning services, prompt marketplaces, or chatbots with marketing departments.

The Top 10 Signal

The highest composite score is 69.0 (Persana AI). No company breaks 70. This is a structurally immature market—high capital, high traction, but shallow autonomy depth. The average Autonomy Depth score across the top 10 is 51.5/100, the weakest dimension by a wide margin. These companies have product-market fit and funding, but the agents themselves are operating at low levels of genuine independence.

Domain Concentration

Software dominates the top 10 (6 companies), followed by Productivity (2) and Health (2). The Health vertical shows an interesting structural divergence: Athelas and careCycle score nearly identically (64.5) but through different paths. Athelas leads on Capital & Defensibility (73); careCycle leads on Autonomy Depth (60). One bet is moated infrastructure, the other is agent sophistication.

First-week baseline: All companies carry the Emerging tier classification. Weekly delta tracking begins W13-2026. The scoring pipeline runs nightly against YC batch data, Crunchbase financials, GitHub commit velocity, and API documentation depth.

W12-2026 Stack Ranking

Top 10 AI agent companies by composite score. Five dimensions: Model Capability (20%), Market Traction (25%), Platform Ecosystem (20%), Autonomy Depth (20%), Capital & Defensibility (15%). Click any row to expand.

# Company Domain Composite Tier Key Signal
1 Persana AI Productivity 69.0 Emerging Highest Market Traction (80) in the index. AI-powered sales prospecting with autonomous lead enrichment and outreach sequencing.
Model Capability75
Market Traction80
Platform Ecosystem65
Autonomy Depth55
Capital & Defensibility70

Structural Signals

  • Highest Market Traction score in the index (80)
  • AI sales agent handles prospecting, enrichment, and outreach autonomously
  • Strong go-to-market in SMB/mid-market sales teams
  • Revenue-generating with clear unit economics
Autonomy Depth (55) is the weakest dimension. The agent executes pre-defined sequences well but lacks multi-step reasoning in ambiguous prospect scenarios. Vulnerable to commoditization as foundation model providers build native sales tools.
2 Fiber AI Software 68.0 Emerging Balanced profile across all five dimensions. AI-powered outbound sales with deep data integration and autonomous campaign management.
Model Capability70
Market Traction75
Platform Ecosystem70
Autonomy Depth55
Capital & Defensibility70

Structural Signals

  • Most balanced score profile in the top 10—no dimension below 55
  • Strong Platform Ecosystem (70) through CRM and data provider integrations
  • Autonomous campaign execution with adaptive messaging

Risk Indicators

  • Shares the same Autonomy Depth ceiling (55) as Persana AI
  • Competitive overlap with multiple YC-backed sales AI companies
3 Warmly Software 66.0 Emerging Highest Capital & Defensibility (70) among Software companies. Autonomous website visitor identification and real-time engagement.
Model Capability65
Market Traction75
Platform Ecosystem70
Autonomy Depth50
Capital & Defensibility70

Structural Signals

  • Real-time visitor deanonymization creates a data moat competitors can't easily replicate
  • Strong integration ecosystem with major CRMs and sales tools
  • Agent triggers engagement autonomously based on visitor behavior signals
Lowest Autonomy Depth (50) in the top 3. The agent reacts to clear behavioral triggers but lacks genuine reasoning about visitor intent in ambiguous sessions.
4 Fini Productivity 65.0 Emerging AI customer support agent with knowledge base integration. Strong Model Capability (70) for intent classification and resolution.
Model Capability70
Market Traction70
Platform Ecosystem65
Autonomy Depth55
Capital & Defensibility65

Structural Signals

  • Autonomous resolution of customer queries without human handoff
  • Knowledge base ingestion allows rapid deployment across verticals
  • Competitive in both SMB and enterprise customer support

Risk Indicators

  • Customer support AI is the most crowded agent category in YC
  • Foundation model providers (OpenAI, Anthropic) shipping native support tools
5 Athelas Health 64.5 Emerging Highest Capital & Defensibility in the index (73). FDA-pathway medical devices combined with AI-driven remote patient monitoring agents.
Model Capability60
Market Traction75
Platform Ecosystem60
Autonomy Depth55
Capital & Defensibility73

Structural Signals

  • FDA regulatory pathway creates a structural moat competitors can't shortcut
  • Hardware + software integration (diagnostic devices + AI monitoring)
  • Revenue from healthcare systems with long-term contracts
  • Highest Capital & Defensibility score (73) in the entire index

Risk Indicators

  • Lower Model Capability (60) reflects constrained autonomy in clinical settings
  • Regulatory compliance limits speed of agent iteration
6 careCycle Health 64.5 Emerging Highest Autonomy Depth (60) in the Health vertical. Patient engagement agents that autonomously manage care coordination workflows.
Model Capability65
Market Traction70
Platform Ecosystem60
Autonomy Depth60
Capital & Defensibility68

Structural Signals

  • Highest Autonomy Depth (60) among Health companies
  • Agent handles multi-step care coordination without constant clinician oversight
  • Patient engagement workflows adapt based on response patterns

Risk Indicators

  • Platform Ecosystem (60) is constrained by healthcare IT fragmentation
  • Competing with established EHR vendors adding agent capabilities
7 Mutiny Software 64.5 Emerging Lowest Autonomy Depth (45) in the top 10 offset by strong defensibility (73). AI-personalized web experiences for B2B conversion.
Model Capability65
Market Traction75
Platform Ecosystem65
Autonomy Depth45
Capital & Defensibility73

Structural Signals

  • Tied for highest Capital & Defensibility (73) alongside Athelas
  • Strong enterprise customer base creates switching cost moat
  • AI personalization generates measurable conversion lift (data defensibility)
Lowest Autonomy Depth (45) in the entire top 10. The "agent" is closer to a sophisticated personalization engine than an autonomous system. The classification is borderline—Mutiny may drop from the agent index in future scoring cycles if autonomy criteria tighten.
8 Daily Software 63.2 Emerging Strongest Platform Ecosystem (70) in the bottom half. Real-time video/audio infrastructure powering agent-to-human interactions.
Model Capability70
Market Traction70
Platform Ecosystem70
Autonomy Depth40
Capital & Defensibility66

Structural Signals

  • Infrastructure play—provides the real-time communication layer other agents build on
  • Three dimensions at 70: Model Capability, Market Traction, Platform Ecosystem
  • Developer-first API with strong documentation and SDK ecosystem
Autonomy Depth (40) is the second-lowest in the top 10. Daily is more "agent infrastructure" than "agent company." The product enables agents built by others rather than deploying its own autonomous systems.
9 Inkeep Software 63.0 Emerging Strong Model Capability (70) for documentation understanding. AI-powered search and support agent that ingests entire knowledge bases.
Model Capability70
Market Traction65
Platform Ecosystem65
Autonomy Depth55
Capital & Defensibility60

Structural Signals

  • Deep document understanding for technical documentation and knowledge bases
  • Agents can autonomously answer developer questions from ingested docs
  • Growing adoption among developer-tools companies for embedded support

Risk Indicators

  • Lowest Capital & Defensibility (60) in the top 10
  • Knowledge base Q&A is a feature that every major platform is building natively
10 QueryPie AI Software 63.0 Emerging Most evenly distributed score in the index—all five dimensions within 10 points of each other. Data access governance with AI-driven policy agents.
Model Capability65
Market Traction65
Platform Ecosystem65
Autonomy Depth55
Capital & Defensibility65

Structural Signals

  • Most balanced profile—all dimensions between 55 and 65
  • Data governance is a structural moat: compliance requirements create sticky adoption
  • AI policy agents enforce access controls autonomously across database systems

Risk Indicators

  • No standout dimension creates a "why this company" narrative for investors
  • Governance tooling is adjacent to major cloud providers' roadmaps
Dimension key: MC = Model Capability (20%), MT = Market Traction (25%), PE = Platform Ecosystem (20%), AD = Autonomy Depth (20%), CD = Capital & Defensibility (15%). All scores out of 100. Composite is the weighted average. No company breaks 70—this is a structurally immature market. Weekly deltas begin W13-2026.

Structural Gaps

Three structural holes in the YC AI agent ecosystem, each representing a category-defining opportunity.

Critical The Autonomy Ceiling

The average Autonomy Depth across the top 10 is 51.5/100—the weakest dimension by a wide margin. Market Traction averages 72.5 while the agents themselves are operating at low levels of genuine independence. This market is selling "agents" that are, structurally, sophisticated automation with LLM-powered decision points.

The gap: Who builds the first agent that scores 80+ on Autonomy Depth while maintaining 70+ Market Traction?

Current leaders optimize for traction first and autonomy second. The company that inverts this—building genuinely autonomous multi-step reasoning systems, then proving market fit—creates a structural moat that "wrapper + traction" companies cannot replicate. This is the difference between Salesforce adding AI features and a company that makes Salesforce itself autonomous.

High The Health Vertical Divergence

Athelas and careCycle score identically (64.5) through structurally different paths. Athelas leads Capital & Defensibility (73 vs. 68); careCycle leads Autonomy Depth (60 vs. 55). This divergence signals a vertical-specific valuation question: in regulated markets, does defensive moat or agent sophistication compound faster?

The thesis: Healthcare agents that combine regulatory moat (FDA/HIPAA) with high autonomy create a category no one else can enter.

Neither company has both. The entity that merges Athelas-style regulatory defensibility with careCycle-style autonomous care coordination creates a structurally unassailable position. This is not a technology gap—it is an organizational and regulatory strategy gap.

Medium The Infrastructure-vs-Agent Identity Crisis

Daily (rank #8) scores 70 across three dimensions but only 40 on Autonomy Depth. Mutiny (rank #7) scores 73 on defensibility but 45 on autonomy. Both are classified as "agent companies" but function more as infrastructure or optimization tools with agent marketing.

The classification question: As scoring criteria tighten, which companies drop out of the agent index entirely?

This matters for investors. A portfolio that thinks it holds 10 "AI agent" positions actually holds 6 agent companies and 4 infrastructure/optimization plays. The structural difference in exit multiples between "agent" and "SaaS with AI features" will widen as the category matures. The companies aware of this distinction are racing to increase their Autonomy Depth scores before the market reclassifies them.

Ecosystem Landscape

How the top 10 distribute across domains, and where the structural concentration reveals opportunity and risk.

Domain Distribution

Software dominates the top 10 with 6 companies, followed by Productivity (2) and Health (2). The Software concentration reflects both the market reality—developer tools and B2B SaaS are the first adopters of agent workflows—and a gap signal: consumer, finance, legal, and education verticals are underrepresented.

Software6 companies
60%
Productivity2 companies
20%
Health2 companies
20%

The Dimension Landscape

Average scores across the top 10 reveal the structural profile of the AI agent market in early 2026.

Market Traction
Strongest dimension. These companies have customers and revenue.
72.5
Platform Ecosystem
Integrations and developer ecosystems are well-established.
65.5
Capital & Defensibility
Funding is available but structural moats are thin for most companies.
67.5
Model Capability
Technical foundations are solid. Most companies leverage frontier models effectively.
67.5
Autonomy Depth
The structural weakness. Agents are not yet deeply autonomous.
51.5

Score Distribution

The top 10 spans only 6 points (63.0 to 69.0). This is an unusually compressed range, indicating that the market has not yet produced a breakaway leader. For comparison, the K-Pop vertical's top 6 spans 24 points (68.5 to 92.15). The AI agent market is structurally undifferentiated.

Three companies share the same composite score at rank 5–7 (64.5 each: Athelas, careCycle, Mutiny), arrived at through entirely different dimensional profiles. This suggests the composite score alone is insufficient for investment decisions—the dimension breakdown is where the signal lives.

The "Traction-First" Pattern

Every company in the top 10 has Market Traction as its strongest or second-strongest dimension. Not a single company leads with Autonomy Depth. This is a market where companies are optimizing for customer acquisition and revenue, then retrofitting autonomy. The structural question: will the market reward this approach, or will a "deep autonomy first" entrant leapfrog the current leaders?

Absent verticals: Finance, Legal, Education, and Consumer are not represented in the top 10 despite significant YC investment in these categories. Either these verticals are earlier in their agent maturation curve, or they are building agent capabilities that do not yet meet the structural classification criteria. This gap is worth monitoring in W13+.

Methodology

Five dimensions, 100-point weighted composite scale. Every score traces to structural evidence.

SBPI Dimensions — AI Agent Vertical

Market Traction (MT)
Revenue growth, customer count, retention metrics, market penetration velocity, competitive win rates
25%
Model Capability (MC)
Technical depth, model architecture choices, fine-tuning sophistication, reasoning chain quality, error recovery
20%
Platform Ecosystem (PE)
Integration breadth, API quality, developer adoption, partner network, third-party tool compatibility
20%
Autonomy Depth (AD)
Multi-step reasoning, tool use sophistication, error handling without human intervention, genuine task independence
20%
Capital & Defensibility (CD)
Funding runway, data moats, regulatory advantages, switching costs, network effects, IP portfolio
15%

Classification Criteria

Of 1,672 AI companies in the YC ecosystem, 677 (40.5%) met the structural criteria for "true AI agent" classification:

  • Autonomous task execution: The system can complete multi-step tasks without human intervention at each step
  • Multi-step reasoning: The system chains decisions across multiple actions, not just single-turn responses
  • Tool integration: The system uses external tools, APIs, or data sources as part of its workflow
  • Persistent state: The system maintains context across interactions and adapts based on prior outcomes

Companies that failed classification were categorized as: chatbot (single-turn), wrapper (thin layer over foundation model), fine-tuning service (model customization, not agent deployment), or platform/infrastructure (enables agents but does not deploy them).

Data Sources

  • YC Company Database: Batch data, founding dates, team size, category classification
  • Crunchbase: Funding rounds, valuations, investor composition, financial signals
  • GitHub: Commit velocity, repository activity, open-source engagement, documentation depth
  • API Documentation: Endpoint coverage, SDK availability, integration breadth, developer experience quality
  • Product Hunt / G2: User reviews, adoption velocity, competitive comparison signals
  • Public Filings & Press: Revenue disclosures, partnership announcements, regulatory filings

Scoring Process

  • Nightly pipeline: Automated extraction from data sources listed above. Each dimension scored independently using structural evidence, not sentiment.
  • Composite calculation: Composite = (MC × 0.20) + (MT × 0.25) + (PE × 0.20) + (AD × 0.20) + (CD × 0.15)
  • Tier classification: W12-2026 is the baseline week. All companies are classified as "Emerging." Tier promotions (Established, Leader) require 4+ consecutive weeks of scoring with upward delta trends.
  • Evidence chain: Every dimension score traces to specific data points. No score is generated without a source document.
Transparency: SHUR IQ publishes the dimension weights, data sources, and classification criteria. The scores are reproducible given the same input data. What is proprietary is the extraction logic—how structural signals are weighted within each dimension, and how the nightly pipeline prioritizes conflicting evidence.