OpenPipe
OpenPipe is a post-training AI platform that enables developers and enterprises to fine-tune LLMs and apply reinforcement learning to build reliable, cost-efficient AI agents for production use cases including research, coding, support, and voice.
- Company typePrivate
- Founded2023
- HeadquartersSan Francisco, United States
- Headcount1–10
- GTM typeB2B
- OfferingSoftware
What OpenPipe does
OpenPipe is a post-training AI platform that enables software developers and enterprises to fine-tune and apply reinforcement learning to large language models for production AI agents. Founded in 2023 by brothers Kyle Corbitt (CEO) and David Corbitt (CPO), the company built a horizontal developer platform with a self-serve app, an open-source RL framework (ART), a label-free reward function (RULER), a managed Serverless RL service, and a fine-tuning product that automatically converts logged production traffic into training data. The company operated a freemium, usage-based model charging per-token rates for training and inference, with enterprise contracts layered on top featuring dedicated solution architects, SLAs, and roadmap influence. Customer segments spanned developer startups, YC portfolio companies, and enterprise accounts including Zapier, Wispr, and Method, with use cases including deep research agents, coding agents, customer support agents, and voice agents. OpenPipe raised $6.7 million in seed funding from Costanoa Ventures and Y Combinator in March 2024, and was acquired by CoreWeave in September 2025 to combine with Weights & Biases into a unified AI development platform. Following the acquisition, OpenPipe's platform features are migrating to W&B, with the legacy platform being deprecated on July 30, 2026.
OpenPipe firmographics
Firmographics- Name
- OpenPipe
- Legal name
- OpenPipe Inc.
- Website
- https://openpipe.ai
- Company type
- Private
- Founded year
- 2023
- Operating status
- Acquired
- Headcount range
- 1–10 employees
- Short description
- OpenPipe is a post-training AI platform that enables developers and enterprises to fine-tune LLMs and apply reinforcement learning to build reliable, cost-efficient AI agents for production use cases including research, coding, support, and voice.
- Ownership category
- akta.pro rank
Where OpenPipe is headquartered
LocationHeadquarters
- HQ city
- San Francisco
- HQ country
- United States
- HQ region
- North America
Offices1 record
Markets served
OpenPipe business model
Business model- GTM type
- B2B
- Offering type
- Software
- Cost components
- Technology or R&D, Infrastructure, Personnel, Marketing or Sales, Operations
Revenue model
- Fine-tuning as a Service: Managed fine-tuning platform where customers log requests, train models, and deploy specialized LLMs. Charges based on model architecture and token count for training.
- Inference API: Model inference performed through OpenPipe API charged at per-token rates. Pricing varies by model. Optional fixed-fee tiers for budget certainty.
- Enterprise Contracts: Enterprise agreements with named solution architects, SLAs, roadmap influence, and volume discounts. Includes consulting engagement for RL solutions.
- Credits System: Accounts may be issued credits for promotional or service-related reasons applied to next invoices.
Pricing tiers
| Model | Billing | Price |
|---|---|---|
| Freemium | Pay-as-you-go | Free tier available for developers to get started |
| Usage-based | Monthly | Usage-based training and inference |
| Subscription | Multi-year contract | Enterprise agreements with contractual SLAs and volume discounts |
Go-to-market motion2 records
Distribution channels3 records
Marketing channels6 records
OpenPipe product offering
Product offeringCore offering
OpenPipe operates a post-training platform for large language models, offering supervised fine-tuning (SFT) and reinforcement learning (RL) services for developers building AI agents. The platform lets customers log real production traffic, generate training datasets, fine-tune and RL-train models, and serve them via an OpenAI-compatible API with on-prem or VPC deployment options. Core products include the Fine-Tuning Platform, the open-source ART RL framework, the RULER reward function, and Serverless RL managed training infrastructure.
Product overview
OpenPipe is a post-training platform for fine-tuning and reinforcement learning that helps developers build reliable AI agents. The core offering consists of the Fine-Tuning Platform for supervised fine-tuning (SFT) and the Agent Reinforcement Trainer (ART) open-source framework for RL-based agent training. Key products include Serverless RL (managed RL infrastructure), RULER (general-purpose automatic reward function), and Mixture of Agents (specialist model chaining). OpenPipe joined CoreWeave in September 2025 and platform features have been migrating to W&B. The company offers solutions for Deep Research Agents, Coding Agents, Customer Support Agents, and Voice Agents, along with enterprise RL consulting services. Open-source tools include ART, RULER, and PII-Redact.
Differentiator
Problem solved
Functional benefit
Brands
- ART (Agent Reinforcement Trainer): Open-source reinforcement learning framework for training LLM-based agents using GRPO, designed for multi-turn agentic workflows.
- RULER
- Serverless RL
- OpenPipe Fine-Tuning Platform
Products and services
- OpenPipe Platform Post-training platform for fine-tuning and reinforcement learning of LLMs. Lets developers evaluate, fine-tune, and serve LLMs through a unified developer experience with an OpenAI-compatible API and on-prem or VPC deployment.
- Fine-Tuning Platform Managed supervised fine-tuning service that automatically logs real production traffic as training data and lets teams fine-tune models such as Llama 3.1, Mistral 7B, Mixtral, Qwen, and GPT-4o Mini.
- Agent Reinforcement Trainer (ART) MIT-licensed open-source reinforcement learning framework for training LLM-based agents using GRPO. Supports multi-turn rollouts, Unsloth GPU memory optimizations, vLLM inference, and OpenAI-compatible endpoints for drop-in integration with existing codebases such as CrewAI, OpenAI Agents SDK, and Mastra.
- Serverless RL Managed reinforcement learning service that handles training and inference infrastructure end-to-end, with every trained checkpoint instantly available through W&B Inference at production-level rate limits and reliability.
- Mixture of Agents (MoA) Model architecture that chains multiple specialist models together to deliver higher accuracy and substantially lower cost than GPT-4, particularly for synthetic training-data generation.
- PII-Redact Open-source, on-device PII redaction package using fine-tuned Llama 3.2 1B models (PII-Redact-Name and PII-Redact-General), achieving 100% SSN detection and 99.8% IP address detection and significantly outperforming Presidio.
- Enterprise RL Solutions Enterprise-grade reinforcement learning consulting and deployment services with strategic discovery, pilot programs, multi-month rollout, and continuous optimization phases, including named solution architects, contractual SLAs, and roadmap influence written into the enterprise agreement.
Quantifiable outcome
- 8x lower inference cost than GPT-4-class APIs
- +6 more outcomes
Companies that use OpenPipe
Customer profileNamed customers6 records
Segments5 records
Ideal customer profiles2 records
OpenPipe technology and API
TechnologyTechnology focussed Yes
API detail
- Has API
- Yes
- API docs
- API detail
Core technology
AI maturity
App detail
Integration6 records
AI capability9 records
Feature7 records
OpenPipe partnerships and signals
Strategic signalPartnerships
Seven partnerships are on record, tiered flagship, core and minor.
- CoreWeaveflagshipCoreWeave acquired OpenPipe to expand beyond GPU infrastructure into the software stack for AI agent training using reinforcement learning. Combined with Weights & Biases to build unified platform for training, evaluating, and observing AI models.
- Weights & BiasescoreSister company under CoreWeave. OpenPipe training and inference migrating to W&B platform. ART integrates with W&B for monitoring training runs, metrics tracking, and model management.
- Logan Kilpatrick (OpenAI)minorKey advisor providing guidance on AI product strategy and development.
- Alex Graveley (GitHub Copilot creator)minorKey advisor with expertise in developer tools and AI coding assistants.
- Tom Preston-Werner (GitHub co-founder)minorKey advisor with deep technical experience in building developer platforms.
- Flo Crivello (Lindy.ai founder)minorKey advisor in AI agent development.
- Immad Akhund (Mercury founder)minorKey advisor with startup scaling experience.
Scale indicators9 records
Recent moves6 records
Expansion highlights6 records
OpenPipe competitors and assessment
Company assessmentDirect peers
- Together AI: Provides managed inference and fine-tuning APIs for open-source LLMs with usage-based pricing. Directly comparable to OpenPipe's inference + fine-tuning platform offering, competing on cost-per-token and developer experience.
- Anyscale: Ray-based platform for distributed AI/RL workloads with managed training and serving. Directly comparable to OpenPipe's Serverless RL and ART framework, serving AI engineers building production agentic systems.
- Fireworks AI: Managed inference and fine-tuning platform for open-source LLMs with enterprise deployment options. Direct peer to OpenPipe on fine-tuning APIs, model serving, and on-prem/VPC offerings.
- Replicate: Cloud platform for running and fine-tuning open-source ML models via API. Comparable to OpenPipe's PLG motion and usage-based pricing, serving developers building production AI applications.
Broad incumbents
- Hugging Face: Open-source AI platform hosting models, datasets, and Spaces with managed inference and fine-tuning. Comparable as a broad incumbent in the developer AI tooling stack that OpenPipe also targets via ART/PII-Redact open-source.
- Lambda Labs: GPU cloud provider with managed fine-tuning services for LLMs. Comparable as a broader incumbent offering both raw GPU infrastructure and fine-tuned model serving overlapping with OpenPipe's stack.
- Scale AI: Data infrastructure and fine-tuning platform for enterprise AI, with strong RLHF capabilities. Comparable to OpenPipe's RL-for-agents positioning, particularly around reward modeling and evaluation, though at much larger scale.
Emerging players
- Predibase: Developer platform for fine-tuning and serving LLMs with RLHF capabilities built on Ludwig. Emerging peer focused on the same enterprise fine-tuning-and-serve workflow OpenPipe addresses, with overlapping RL tooling.
- Modal: Serverless compute platform optimized for AI/ML workloads including training and inference. Comparable to OpenPipe's Serverless RL positioning on developer-friendly, GPU-efficient infrastructure for AI agents.
- Mistral AI: Open-weight LLM provider with fine-tuning APIs for its own model family. Comparable to OpenPipe on the fine-tuning side for Mistral models specifically, though primarily a model provider rather than a fine-tuning infrastructure layer.
Market position
Strengths5 records
Weaknesses5 records
Competitive moat5 records
Key risks6 records
Key highlights7 records
Customer concentration
OpenPipe social profiles
Digital presenceOpenPipe compliance and trust
Trust signalCompliance3 records
OpenPipe financial estimates
Financial estimateRevenue estimate
Valuation estimate
OpenPipe leadership team
Management profileNumber of profiles
Profiles2 records
OpenPipe funding detail
Funding detailFunding overview
Funding rounds2 records
Investors4 records
Funding detail is available on the Subscription and Enterprise plan.Contact sales →
OpenPipe M&A and investment
M&A and investmentM&A
Investments
M&A and investment is available on the Subscription and Enterprise plan.Contact sales →
Frequently asked questions about OpenPipe
What does OpenPipe do?
OpenPipe operates a post-training platform for large language models, offering supervised fine-tuning (SFT) and reinforcement learning (RL) services for developers building AI agents. The platform lets customers log real production traffic, generate training datasets, fine-tune and RL-train models, and serve them via an OpenAI-compatible API with on-prem or VPC deployment options. Core products include the Fine-Tuning Platform, the open-source ART RL framework, the RULER reward function, and Serverless RL managed training infrastructure.
Is OpenPipe a public or private company?
OpenPipe is a private company. It is classified as corporate owned and is currently acquired.
When was OpenPipe founded?
OpenPipe was founded in 2023. It employs 1 to 10 people.
Where is OpenPipe based?
OpenPipe is headquartered in San Francisco, United States, in the North America region.
How does OpenPipe make money?
Four revenue lines are on record. Fine-tuning as a Service is the primary driver. The others are inference API, enterprise Contracts and credits System.
Who are OpenPipe's main competitors?
Direct peers on record are Together AI, Anyscale, Fireworks AI and Replicate. Broad incumbents are Hugging Face, Lambda Labs and Scale AI. Emerging players are Predibase, Modal and Mistral AI.
Does OpenPipe have an API?
Yes. OpenPipe provides an OpenAI-compatible chat completion API that allows developers to use their fine-tuned models with existing code expecting OpenAI format. The API supports both inference (model serving) and training endpoints. Training and inference via OpenPipe API is charged at per-token rates with volume discounts. The legacy OpenPipe platform will stop supporting new training and inference on July 30, 2026, with migration to W&B Inference. Developer documentation is at docs.openpipe.ai.