Vellum

Name: Vellum
Brand: Vellum
Rating: 4.8 (20 reviews)

AI Native

Agents for everything. Except self control.

Est 2023|Valuation $90M|Raised $24.5M|33 Ref Customers

LinkedIn 7K|Website|Web traffic 245K|FTEs 37|HQ New York, New York, US

MarketsAI Assistant Agent Builder Platforms LLM Observability

01Competitive Landscape

| Aspect | Vellum | LangSmith (LangChain) | Langfuse | |--------|--------|-----------------------|---------| | Starting Price | Base: Free; Pro: paid tiers with a credits-based personal assistant SKU; vendor-published pricing applies | Developer/entry tier available; commercial tiers with published per-seat pricing plus usage-based fees | Published base fee plus usage-based units; hobby/free tier available | | Best For | Teams wanting a combined prompt/workflow/eval/deploy environment; individuals wanting an always-on assistant with memory/tools | Teams committed to LangChain/LangGraph and wanting tracing/evals integrated into that ecosystem | Teams wanting open-source-friendly tracing/evals/prompt management, flexible deployment, and usage-based scaling | | Key Strength | Side-by-side prompt/model iteration + workflows (per user review); credit-based pass-through claims for model costs (personal assistant) | Tight integration with LangChain suite; mature tracing/evals | Strong OSS posture and explicit data-region options; transparent unit-based pricing | | Key Weakness | Brand/positioning ambiguity (personal assistant vs platform) + review confusion with unrelated “Vellum” products; limited public detail on enterprise SSO/SCIM | Seat-based pricing can scale with team size; ecosystem lock-in concern | Self-hosting operational burden; usage-based “capture everything” risk exists in observability tools generally | - Pricing comparison: value proposition vs alternatives - Vellum personal assistant has a relatively low entry point but potentially variable monthly spend due to credits and background tasks. (Vendor pricing documentation) - LangSmith uses per-seat pricing plus usage-based fees for traces and related services. (Vendor pricing documentation) - Langfuse uses a base fee plus usage units, with a free/hobby tier and published retention/throughput tiers. (Vendor pricing documentation) - Customer testimonials comparing products - Community discussion frames Vellum as a “ten-minute install alternative” to other agent frameworks (anecdotal; not a structured comparison). (Industry Reddit and community threads) - Market share and adoption trends - No authoritative market-share numbers were found in accessible sources. - Tech press snapshots suggested early traction with a small paying customer base at seed stage, but those reports are dated and largely self-reported. (Tech press coverage) - When customers choose competitors instead (and why) - LangSmith: chosen when teams are standardized on LangChain/LangGraph. - Langfuse: chosen when open-source/self-host and regional data residency are key. - Promptfoo: chosen when teams focus on evals/red-teaming/testing in CI or want local/self-host workflows. (Product documentation and community pages)

01Competitive Landscape

Aspect	Vellum	LangSmith (LangChain)	Langfuse
Starting Price	Base: Free; Pro: paid tiers with a credits-based personal assistant SKU; vendor-published pricing applies	Developer/entry tier available; commercial tiers with published per-seat pricing plus usage-based fees	Published base fee plus usage-based units; hobby/free tier available
Best For	Teams wanting a combined prompt/workflow/eval/deploy environment; individuals wanting an always-on assistant with memory/tools	Teams committed to LangChain/LangGraph and wanting tracing/evals integrated into that ecosystem	Teams wanting open-source-friendly tracing/evals/prompt management, flexible deployment, and usage-based scaling
Key Strength	Side-by-side prompt/model iteration + workflows (per user review); credit-based pass-through claims for model costs (personal assistant)	Tight integration with LangChain suite; mature tracing/evals	Strong OSS posture and explicit data-region options; transparent unit-based pricing
Key Weakness	Brand/positioning ambiguity (personal assistant vs platform) + review confusion with unrelated “Vellum” products; limited public detail on enterprise SSO/SCIM	Seat-based pricing can scale with team size; ecosystem lock-in concern	Self-hosting operational burden; usage-based “capture everything” risk exists in observability tools generally

Pricing comparison: value proposition vs alternatives
- Vellum personal assistant has a relatively low entry point but potentially variable monthly spend due to credits and background tasks. (Vendor pricing documentation)
- LangSmith uses per-seat pricing plus usage-based fees for traces and related services. (Vendor pricing documentation)
- Langfuse uses a base fee plus usage units, with a free/hobby tier and published retention/throughput tiers. (Vendor pricing documentation)
Customer testimonials comparing products
- Community discussion frames Vellum as a “ten-minute install alternative” to other agent frameworks (anecdotal; not a structured comparison). (Industry Reddit and community threads)
Market share and adoption trends
- No authoritative market-share numbers were found in accessible sources.
- Tech press snapshots suggested early traction with a small paying customer base at seed stage, but those reports are dated and largely self-reported. (Tech press coverage)
When customers choose competitors instead (and why)
- LangSmith: chosen when teams are standardized on LangChain/LangGraph.
- Langfuse: chosen when open-source/self-host and regional data residency are key.
- Promptfoo: chosen when teams focus on evals/red-teaming/testing in CI or want local/self-host workflows. (Product documentation and community pages)

Aspect

Vellum

LangSmith (LangChain)

Langfuse

Starting Price

Base: Free; Pro: paid tiers with a credits-based personal assistant SKU; vendor-published pricing applies

Developer/entry tier available; commercial tiers with published per-seat pricing plus usage-based fees

Published base fee plus usage-based units; hobby/free tier available

Best For

Teams wanting a combined prompt/workflow/eval/deploy environment; individuals wanting an always-on assistant with memory/tools

Teams committed to LangChain/LangGraph and wanting tracing/evals integrated into that ecosystem

Teams wanting open-source-friendly tracing/evals/prompt management, flexible deployment, and usage-based scaling

Key Strength

Side-by-side prompt/model iteration + workflows (per user review); credit-based pass-through claims for model costs (personal assistant)

Tight integration with LangChain suite; mature tracing/evals

Strong OSS posture and explicit data-region options; transparent unit-based pricing

Key Weakness

Brand/positioning ambiguity (personal assistant vs platform) + review confusion with unrelated “Vellum” products; limited public detail on enterprise SSO/SCIM

Seat-based pricing can scale with team size; ecosystem lock-in concern

Self-hosting operational burden; usage-based “capture everything” risk exists in observability tools generally