Flow AI — for LLMs and AI agents

# Flow AI – Data Agent Infrastructure
The harness for building production-grade analytical AI agents on your data product: data catalog, typed plans, embedded runtime, Studio, and self-improvement.

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# Ship production-grade analytical AI agents
The harness for building powerful AI agents on top of your data product.

[ Problem ]

## Your product has rich data. Agents still can’t do real work with it.
- Complex schemas
- Cryptic column names
- Thousands of enums
- Data quality issues
- Temporal rules
- Domain formulas

### The meaning of the data lives outside the schema
Metric definitions, formulas, temporal rules, tenant logic, and exceptions are scattered across docs, dashboards, and people’s heads.

### Actions turn agent mistakes into product risk
Agents trigger jobs, update records, and run simulations. Without permissions and approvals, a bad interpretation becomes a product incident.

### Generic agent loops break customer-facing products
Open-ended tool exploration burns tokens and adds latency. “Eventually correct” is too slow and breaks the user experience.

[ Platform ]

## A purpose-built harness to make your data product AI-native
flowai-harness gives engineering teams production-ready defaults for agents that reason across complex data environments, plan reliably, and execute actions safely.

**The five primitives:**
- Data
- Plans
- Runtime
- Studio
- Self-improvement

[ Platform ]

## The five primitives

### Data: Data catalog for AI agents
Profile databases and organizational knowledge into one searchable graph of tables, columns, joins, metrics, and docs. Agents use it to resolve intent, find the right data, and ground queries in tenant-scoped context.

### Plans: Primitives for safe action execution
Define typed plan and action schemas. The runtime validates the plans and runs them as state machines. Plans are persisted and status is tracked for full auditability.

### Runtime: A runtime for data-heavy agents
A Rust-native harness for analytical agents, built on our high-performance agent framework. It brings plans, approvals, tools, evaluations, and context management into one fast runtime.

### Studio: Run, debug, evaluate, and improve agents
Flow AI Studio is the native UI for Flow AI agents: inspect runs, traces, evals, and changes from one workspace. Use the dev Studio locally, then move to Enterprise Studio for production teams.

### Self-improvement: Propose, test, promote, repeat (coming soon)
Turn eval failures, traces, and near misses into improvement candidates. Each candidate runs in isolation, is scored against your benchmark, and either becomes the new baseline or informs the next research wave.

[ Integrations ]

## Works with the stack you already run
Bring your own models, warehouse, and cloud. Flow AI runs inside your infrastructure — your keys, your region, no data leaving your systems.

| Feature | Specification |
| :--- | :--- |
| Models | OpenAI, Anthropic, Gemini, Llama, Mistral, Qwen, and more |
| Data | Postgres, Snowflake, BigQuery, Databricks, DuckDB |
| Clouds | AWS, Azure, GCP |
| Deployment | On-premise or SaaS |
| Data residency | EU or US |

[ About us ]

## Built by early pioneers in agentic AI
From the original generative writing assistant to industry-leading evaluation models, we've spent years turning LLMs into reliable, real-world products.

### Backed by
- Project A
- Seedcamp
- Lifeline
- Moonfire

[ Get started ]

## Build the first production agent with Flow AI.
Start with the documentation, or book a demo with the founders.

## Links
[Flow Judge](/judge)
[Blog](/blog)
[About](/about)
[Legal](/legal)

© 2026 Flow AI