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Casper Labs
Founded 2018 · 58 employees on LinkedIn · 12 known investors
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Prove AI provides observability and auditing tooling for multi-agent AI systems, letting AI engineers trace how and why agents reach decisions, evaluate outcomes at runtime, and replay candidate fixes against trace archives to catch regressions. It aims to make AI outcomes explainable, traceable, and cost-efficient while keeping a human in the loop.
Also known as CasperLabs · Prove AI
Founders & leadership
Casper Labs was founded in 2018 by Mrinal Manohar.
Investors · 12
How we know: Digital Strategies's portfolio page · Not right? Tell us
How we know: Draper Goren Blockchain's portfolio page · Not right? Tell us
How we know: Saxon's portfolio page · Not right? Tell us
How we know: Woodstock Fund's portfolio page · Not right? Tell us
How we know: ZMT Capital's portfolio page · Not right? Tell us
How we know: the VCSheet dataset · Not right? Tell us
Company profile
researched Aug 2026Prove AI, operating at casperlabs.io, develops tooling aimed at making outcomes produced by multi-agent AI systems correct, explainable and auditable. The company frames the problem as AI agents running on infrastructure that does not support provable or traceable troubleshooting, leaving basic operational questions — such as the anticipated cost per workload and how and why a given agent reached a decision — difficult and time-consuming to answer.
The product is organized around three capabilities: consolidated token-level cost intelligence across multiple AI platforms and vendors through a single hub; runtime evaluation of AI decisions so that the path to a specific outcome can be demonstrated; and replay of candidate fixes against archived traces to detect silent regressions before changes ship. The company also positions human-in-the-loop review as central to its approach, describing its tooling as a way to surface and operationalize human expertise inside AI systems in a predictable and cost-controlled manner.
Founding story
The team describes building the tool it wished it had, having experienced multi-agent troubleshooting problems firsthand.
Business model
The company offers software tooling for engineering teams operating multi-agent AI systems; it invites prospective users to contact its technical team rather than publishing self-serve pricing.
▸Full profile — market position, technology, go-to-market, history
Market position
Presents itself as building a sustainable management framework for multi-agent AI systems, motivated by the expectation that token usage patterns are unsustainable and AI operating costs will rise.
The company positions itself against what it describes as legacy infrastructure underlying AI agents, emphasizing provable, traceable troubleshooting, cost-per-token visibility across vendors, and human-in-the-loop oversight.
Technology
Tooling for AI-native troubleshooting comprising token-level cost intelligence aggregated across platforms and vendors, runtime tracing and evaluation of agent decisions, and replay of candidate fixes against stored trace archives to surface regressions.
Go-to-market
Direct outreach and consultative engagement, with "talk to us" and "get in touch" contact paths for its technical team, alongside a Discord community (M.A.S.E.) for AI engineers to discuss multi-agent troubleshooting challenges and provide product feedback.
AI engineers and engineering teams running multi-agent AI systems, including production deployments at large enterprises.
History
The team's stated prior experience includes automating billions of dollars in purchasing decisions at Amazon using reinforcement learning, architecting production multi-agent infrastructure for Fortune 500 deployments, and scaling engineering organizations at a Y Combinator-backed fintech unicorn.
Compiled by commissioned research from 7 cited public sources — announcements, filings, and press listed under research sources below.
Key figures
latest reportedCompany-reported or press-reported figures, each dated to when it was claimed — not independently audited.
▸Research sources · 7
primary sources listed
- The future-proof blockchaincasperlabs.io · web
- Sleep Startup Casper Raises $55 Million in Series B Fundingprnewswire.com · web
7 public sources were cited for this profile; the first-party ones are listed here.
Frequently asked questions
- What does Casper Labs do?
- Prove AI builds observability and troubleshooting tooling that makes multi-agent AI system outcomes traceable and auditable.
- Who founded Casper Labs?
- Casper Labs was founded by Mrinal Manohar in 2018.
- Who are Casper Labs's investors?
- Casper Labs's investors include Arrington Capital, Digital Strategies, Draper Goren Blockchain, Mapleblock Capital, Pentos Ventures, Saxon, Sora Ventures, Spark Digital Capital and 4 more.