P
Awaira Score
55
Out of 100
Valuation
N/A
Post-money
Total Raised
$16M
All rounds
Awaira Score
55/100
Founded
2021
50-200 employees
What They Build
March 2026Predibase provides a fine-tuning and deployment platform purpose-built for large language models, enabling engineering teams to adapt open-source foundation models to their specific domains and production requirements without building the supporting infrastructure from scratch. The platform includes LoRA-based fine-tuning, evaluation pipelines, and a dedicated serving layer optimized for fine-tune…
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StageSeries A
Employees50-200
Country🇺🇸 United States
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Funding Rounds
Series A · No public funding round data available yet.
Founded Same Year (2021)
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View all alternatives to Predibase →Frequently Asked Questions
What is Predibase's valuation?▾
Predibase's valuation is not publicly disclosed.
Who invested in Predibase?▾
Investor information for Predibase is not publicly available at this time.
When did Predibase last raise funding?▾
No public funding round data is currently available for Predibase.
How many employees does Predibase have?▾
Predibase has approximately 50-200 employees.
What does Predibase do?▾
Predibase provides a fine-tuning and deployment platform purpose-built for large language models, enabling engineering teams to adapt open-source foundation models to their specific domains and production requirements without building the supporting infrastructure from scratch. The platform includes LoRA-based fine-tuning, evaluation pipelines, and a dedicated serving layer optimized for fine-tuned model latency.\n\nThe company raised approximately 16 million USD and serves teams at enterprises and growth-stage companies that have concluded that generic LLM APIs are insufficient for their accuracy requirements and want domain-adapted models they own rather than rent. Predibase is built on top of Ludwig, an open-source declarative ML framework developed at Uber and maintained by the same team.\n\nThe fine-tuning market is growing as production AI teams discover that base models underperform on specialized tasks and that instruction fine-tuning on domain-specific data meaningfully improves output quality. Predibase competes with Modal, Anyscale, and cloud-native fine-tuning services, but its focus on the complete workflow from training through serving rather than raw compute rental positions it closer to a managed ML platform than an infrastructure provider.