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AI agents

Roark

Roark helps teams test, monitor, and improve their voice agents. Voice AI is exploding, but reliability is still the #1 challenge. Teams spend hours manually testing agents and still miss failures. In the last 6 months, Roark has processed over 10M minutes of calls, powering monitoring and simulation for teams across the Voice AI ecosystem (including YC companies). We close that gap by combining: 📊 Monitoring & Evaluation - 40+ built-in metrics (latency, instruction-follow, sentiment, etc.), cu

sources
1
Evidence entries preserved.
affiliations
1
Y Combinator
competitors
6
Mapped from High Signal graph features.
status
generated
D1 lookup
last updated
2026-07-15
16:41 UTC
source evidence
Why this company exists here

Y Combinator

yc-company-directory #5703

Roark helps teams test, monitor, and improve their voice agents. Voice AI is exploding, but reliability is still the #1 challenge. Teams spend hours manually testing agents and still miss failures. In the last 6 months, Roark has processed over 10M minutes of calls, powering monitoring and simulation for teams across the Voice AI ecosystem (including YC companies). We close that gap by combining: 📊 Monitoring & Evaluation - 40+ built-in metrics (latency, instruction-follow, sentiment, etc.), cu

source
generated read
High Signal interpretation

Roark is classified as AI agents from source descriptions and fund-directory context. Similar companies below are ranked from offline product facets and meaningful description overlap; category and source affiliation can only strengthen an existing product match. For lookup-created rows, the profile starts as pending enrichment until deeper source collection runs.

offline extraction
Product facets
Voice AIvoice agents
mapping method
Similarity graph

Local clusters rerank extracted product concepts and description terms. The generated graph remains the fallback for sparse descriptions: offline reciprocal product-similarity graph: extracted concepts + description terms + bounded category/affiliation boosts. Minimum fallback score: 0; max competitors: 6.

discovery cluster

Companies similar to Roark

AI agents · 6 peers

A deterministic local cluster built from offline product facets and meaningful description terms. Category and selected-institution affiliation provide bounded tie-breaks. Open any peer to continue exploring its cluster.

Cactus

match 65

HVAC, plumbing, roofing, and electrical companies spend $3K–$25K every month making the phone ring - then lose 10–20% of those leads to slow response times, missed calls, and zero follow-up. The revenue was already there. It just walked out the back door. Cactus closes that gap on both sides. Inbound: Every call answered in under 60 seconds, 24/7 qualified and booked directly into Housecall Pro, Jobber, FieldEdge, or ServiceTitan. No voicemails. No missed jobs. Outbound: Warm leads, dormant cust

shared product terms: companie, spend, month, miss; shared affiliation: Y Combinator

Coval

match 54

Coval is a simulation & evaluation platform for autonomous AI agents, helping engineers launch dependable assistants across chat, voice, and other modalities. We simulate thousands of scenarios engineers don't have to manually test their agents. Our CI/CD evaluations automatically simulate and detect regressions.

shared extracted concept terms: voice; shared product terms: simulation, evaluation, voice, manually; same category: AI agents; shared affiliation: Y Combinator

MOVEdot

match 44

Our agents run hardware engineering tasks that normally take hours or days in just a few minutes, allowing engineers to process 100x more data and information. Our platform allows hardware engineers to orchestrate agents for tasks such as analyzing failures across entire test campaigns, pulling the right data and KPIs from their databases, checking how conditions (like temperature or load) affect performance and reliability, and then document findings in reports and dashboards.

shared product terms: hour, minute, failure, test; same category: AI agents; shared affiliation: Y Combinator

Lemma

match 44

Lemma catches the silent, semantic failures your observability tools miss, where your AI agent looks like it worked but didn’t. We scan every trace to surface issues before users complain, identify root causes, and help you fix them without manual digging, so your agents improve over time.

shared product terms: failure, miss, but, improve; same category: AI agents; shared affiliation: Y Combinator

Cohesion

match 44

Cohesion is building AI agents for hedge funds. Our agents track earnings and non-traditional datasets like podcasts and X/twitter. Analysts spend hours a week manually tracking these data sources and still miss relevant investing signals. Now, our agents do it for them autonomously.

shared product terms: spend, hour, manually, still; same category: AI agents; shared affiliation: Y Combinator

Ashr

match 44

Ashr is a fully contained test and evals platform that improves AI agents by ensuring accuracy and quality across a wide range of user journeys through your product. Ashr generates user journeys through your agents’ tool calls, results, and questions. We don’t generate one off tests, we generate large amounts of authentic user stories through your product, and pick up on errors, inconsistencies, and failures that would otherwise take hours of manual testing or get caught by a customer. We also w

shared product terms: test, improve, hour, failure; same category: AI agents; shared affiliation: Y Combinator