Everything you need to build, deploy, and operate production AI agents.
SDKs, runtime services, CLI tools, and AI-assisted development—all designed to work together.
FireFoundry is built for AI-assisted development. Install the CLI and skills, then let your AI coding assistant guide you through the rest.
FireFoundry runs on Kubernetes—locally via minikube or on any cloud provider. Most developers start local. Your AI assistant can help install anything you're missing.
Standalone executable—no Node.js or npm required. Skills add FireFoundry knowledge to Claude Code, Cursor, Windsurf, and VS Code.
The installed skills teach your AI assistant FireFoundry's SDK patterns, CLI commands, service configuration, and deployment workflows.
Your AI assistant handles cluster setup, SDK patterns, service configuration, broker routing, build and deploy cycles—and troubleshooting when things go wrong.
"Add image generation"
Configures model routing, provider credentials, and blob storage.
"Add a structured output bot"
Implements Zod schemas, prompt templates, and model pool routing.
"Deploy and test this"
Builds, deploys to your cluster, and verifies health checks.
Six integrated layers that give you everything you need. Each layer is designed to work seamlessly with the others.
Runtime infrastructure that hosts and operates your agents.
Deploy and operate from CLI or web console.
TypeScript libraries for building and consuming agents.
Utilities that accelerate development.
Pre-built components ready to use.
Skills for Claude Code, Cursor, and more.
Stop cobbling together services. Start building agents.
Every AI provider has outages. Hardcoding a single provider means your app goes down when they do. FireFoundry's industrial-grade broker routes text completions and image generation across providers—with capacity management, QoS tiering, and performance tracking built in.
Configure model groups and failover in the console
Build sophisticated workflows with the entity graph
Complex agents need state machines, multi-step workflows, and human-in-the-loop approvals. You're stitching together queues, databases, and retry logic. When something fails, you start over.
AI agents generate and execute code. One mistake exposes your infrastructure. You're building sandbox after sandbox, reimplementing security controls, and hoping you didn't miss an edge case.
Configure sandbox profiles for different use cases
Search and explore full request telemetry
When your AI agent gives a wrong answer, you can't explain why. Logs are scattered across services. Debugging production AI takes hours of detective work—and you still might not find the root cause.
"It worked in staging" means nothing when your system is non-deterministic. You can't write reliable tests when the LLM returns different answers each time. CI/CD pipelines become a source of anxiety.
Interactive playgrounds for testing and debugging
AI automatically investigates incidents and suggests fixes
Managing AI systems shouldn't require another AI team. When incidents happen, you're manually correlating logs across services. Setting up the platform means reading docs and hoping you got it right.
LLMs hallucinate. Your agents need facts from your documents, real-time web data, and structured knowledge. You're building extraction pipelines, embedding services, and retrieval systems from scratch.
Test retrieval quality with the knowledge base playground
Test and debug long-running virtual workers
Tools like Claude Code, Codex, and Gemini CLI are transforming development. FireFoundry orchestrates these same powerful agents in your cloud—with access to your intranet, sensitive data, and internal systems. Add advanced workflows, triggers, and enterprise controls on top.
We're an AI company building for AI developers. We don't just write documentation—we provide skills that help AI coding assistants help you.
With FireFoundry skills installed, your AI assistant knows exactly how to structure agent code, which decorators to use, and best practices for production agents.
> "Build me a customer service agent that uses our product KB"
@Bot({ name: 'support-bot', modelGroup: 'fast-chat', knowledgebases: ['product-docs'] }) export class SupportBot { async respond(input: string) { return (await this.chat(input)).content; } }
Step-by-step tutorials that build real applications. Each tutorial has a companion demo app you can deploy.
End-to-end document processing pipeline with AI review workflows and SSE streaming.
Multi-bot pipeline with image generation, parallel processing, and PDF assembly.
Tool-calling agent with Data Access Service integration for SQL analysis.
AI-driven data analysis with code generation, secure sandbox execution, and Data Access Service integration.
Full CRM with entity graph modeling, structured output bots, Next.js GUI, BFF authentication, and notification service integration.
Web search and AI analysis agent with structured output and Next.js frontend.
Working Memory integration with drag-and-drop file uploads and processing.
Real code examples from the AgentSDK.
import { GeneralBot, PromptGroup, Prompt, PromptTemplateTextNode, RegisterBot, } from '@firebrandanalytics/ff-agent-sdk'; const systemPrompt = new Prompt({ role: 'system', static_args: {} }); systemPrompt.add_section(new PromptTemplateTextNode({ content: () => 'You are a sentiment analysis assistant. ' + 'Return JSON: { summary, findings[], confidence }', })); const userPrompt = new Prompt({ role: 'user', static_args: {} }); userPrompt.add_section(new PromptTemplateTextNode({ content: (request) => `Analyze: ${request.input}`, })); @RegisterBot('SentimentBot') export class SentimentBot extends GeneralBot { constructor() { super({ name: 'SentimentBot', modelPoolName: 'fast-chat', promptGroup: new PromptGroup([ { name: 'system', prompt: systemPrompt }, { name: 'input', prompt: userPrompt }, ]), }); } }
@RegisterBot makes this bot discoverable by the entity framework. Prompts are composed from typed template nodes, and the model pool routes requests through the Broker for failover and load balancing.
The console gives you complete visibility into your agents.
Interactive playgrounds for testing agents
Browse all deployed applications and their status
Visual entity graph for exploring data
Manage external service integrations
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