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Benchmarking LLMs on Enterprise-Specific Tasks11-50 Employees
  • B2B
  • Early Stage
    Startup in initial stages
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Benchmarking LLMs on Enterprise-Specific Tasks
Measuring model ability is the most challenging part of creating applications that are capable of automating any given part of the economy. There are no good techniques or benchmarks for evaluating LLM performance on business-relevant tasks, so adoption for enterprise production settings has been limited (see Wittgenstein’s ruler).

This problem materializes in each place where LLMs have potential: in understanding whether the AI tool companies are building a product will satisfy a customer demand, determining how feasible models and vendors are for a given enterprise in making purchasing decisions, for researchers who need a north star to which to expand model ability.

Today, answering these questions amounts to hiring a human review team to manually evaluate model outputs. This is prohibitively expensive and slow.

Vals AI is building the enterprise benchmark of LLM and LLM apps on real-world business tasks. In doing so we are creating the infrastructure + certification to automatically audit LLM applications, verifying they are ready for consumption.

We've raised mid-seven figures from some of the top institutional investors and strategic angels in Silicon Valley. See our benchmarks and launch announcement in Bloomberg: bloomberg.com/news/newsletters/2024-04-11/this-startup-is-trying-to-test-how-…
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Langston Nashold
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Stanford CS, Andrew Ng's AI + Climate Change Lab, prev @ Hudson River Trading, Meta, NVIDIA, Snap, Salesforce.
Rayan Krishnan
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Valuation

$0

Funded over

1 round

Latest round

Seed (Jul 2024)

Health insurance

Dental insurance

401k

Substantial equity grants

Free lunch and dinner

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