Company profile
Vellum
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Prompt engineering startup Vellum.ai raises $5M as demand for generative AI services scales | TechCrunch. Jul 11, 2023. Company Launches. Vellum for Agents. See ...
11-50
Series A ($20M)
AI Classification
Vellum is a New York-based AI agent and assistant platform founded in 2023 that enables individuals and non-technical teams to automate work through natural language-driven agents integrating with tools like Slack, email, and app development. Originally positioned as an LLM developer platform, the product has evolved toward broader agent productivity targeting Sales, Ops, Marketing, and Finance users.
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Vellum is one of 2,671 B2B companies in the Kustiq directory.
Vellum sits among 114 ai / ml platform companies in our Data & AI directory.
Similar profiles: Copy, Dagger, Convex, and Market Research Services & Reports.
Both sit in the 11-50 headcount band, and both are at Series A. See Vellum vs Copy side by side.
Both sit in the 11-50 headcount band, and both are at Series A. See Vellum vs Dagger side by side.
Both sit in the 11-50 headcount band, and both are at Series A. See Vellum vs Convex side by side.
How Vellum compares with other AI/ML Platform companies
Vellum is one of 114 AI/ML Platform companies profiled in the Kustiq DataAI directory, which holds 242 DataAI companies in total. Every number below is computed from those profiles.
Vellum sits in the 11-50 headcount band. 23% of the 93 segment peers with a known team size are smaller. 24% of those peers share the same band.
The most common tech detections across the 32 peers with a visible stack are Next.js (47%), Vercel (44%), and Google Analytics (38%). Vellum lists none of them.
Among the 58 segment companies with disclosed funding, Growth is the most common stage (36%). Vellum is at Series A.
The median founding year across 32 peers with a known founding date is 2019.
Toronto is the most common HQ city in this segment, home to 11% of the 18 peers with a known location.
Benchmarks are recomputed from live directory data, so they move as profiles refresh. Counts cover Kustiq-profiled companies, not the whole market.
How this profile was built
- Live web rendering via Browserless headless Chrome, not a stale cached scrape.
- Search intelligence via Serper API across the company site, LinkedIn, press, and GitHub.
- Claude only picks the buckets. It never decides facts.
- 12-factor churn engine. Deterministic score, zero LLM at scoring time.
- SMTP RCPT TO handshake on every contact, at delivery time on full profiles (paid plan).
This profile was built from search coverage across the live web on .
Read the full methodology in our LLM-readable reference or compare against the deterministic-vs-AI framework.
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