FireFoundry console — Broker Configuration, showing providers, model deployments and model groups with their routing strategies — FireFoundry consoleFireFoundry console · Broker configuration

FireFoundry console — Entity Graph, showing a completed run's entity hierarchy with per-node overview, input, output, logs, progress and working memory — FireFoundry consoleFireFoundry console · Broker configuration

FireFoundry Platform

The Enterprise AI Operating Environment.

Every enterprise will have one — by accident or by design. Firebrand builds, governs, and runs yours on FireFoundry.

>80%

Productivity improvement

>2×

Throughput

4 mo

To value

Powering AI at enterprise leaders

HarvardU.S. VentureMidOceanGHR HealthcareAnthony'sStagwellRenovoFedEx

The Problem

Pilots are easy. Production is the hard part.

Most enterprise Gen AI stalls the same way: a promising demo built on stitched-together frameworks, no governance layer underneath, and nobody accountable when it breaks. The distance between a working pilot and a governed production system is where programs die.

95%

of enterprise GenAI pilots fail to reach production with measurable ROI

Source: MIT, State of AI in Business 2025

The Choice

You will have an AI operating environment. The question is how it gets built.

Path one

Assembled by accident

A framework here, a gateway there — each team stitches its own stack of tools that were never designed to run together.

Observability, evals, and governance bolted on after the fact — if at all.

Your team owns the glue code, the upgrades, and the 2 a.m. failures.

Every new model, vendor, or regulation reopens the architecture.

Accountability: diffused across vendors and teams

Path two

Built on purpose — FireFoundry

One governed control plane: orchestration, reliability, human-in-the-loop approvals, and monitoring in a single system.

Deployed in your tenant, integrated with your identity, data, and security controls.

Upgrades, evals, and model changes managed on the platform — not in glue code.

Forward-deployed Firebrand engineers ship alongside your team.

Accountability: a named partner, measured on outcomes

FireFoundry

One control plane for the whole lifecycle.

Build, govern, scale, and monitor every Gen AI application from the same governed surface.

Model your domain as typed entities, put reasoning in bots, and coordinate them with workflows — each piece testable on its own before anything ships.

Agent bundle

Entities

typed state + methods · Zod schemas

Bots

prompts · tool specs · dispatch table

Runnables & Waitables

typed invocation · bidirectional streaming

Workflows

fan-out / fan-in · retries · supervision

Composed from

Knowledge basesCustom skillsAssetsVirtual workersFunction library

Proven before it ships

Bot · KB · VW playgrounds

iterate against live services

Test suites + mock cache

replayable, deterministic runs

Platform + People

The platform runs your AI. Our engineers ship it with you.

FireFoundry is delivered by forward-deployed Firebrand teams who build in your environment and stay accountable after go-live.

In your tenant, under your control

Deployed inside your cloud boundary, on your identity and data controls — never a black box outside your walls.

Governed and reliable from day one

Approvals, policy enforcement, and monitoring are built in — not bolted on after something breaks.

Outcomes owned by a named team

Measurable targets, reviewed quarterly, with one team answerable for them.

Built with the ecosystem you already run

MicrosoftOpenAIAWSDatabricks

See FireFoundry running on your data.

A working session with a Firebrand engineer — your use case, your environment, your governance requirements.

Book a demo →