Insights on building and operating production AI agents.
Thought Leadership
Today we're launching FireFoundry, the enterprise platform for building, deploying, and operating production AI agents. Learn about our vision for making AI agents reliable, observable, and ready for the real world.
FireFoundry Team
Product
Data sovereignty, compliance, cost control, and operational independence. The case for self-hosted AI agents over hosted platforms.
RPA handles the happy path. AI agents handle reality. How intelligent workflow automation goes beyond scripts to reason through exceptions.
How the Notification Service enables email, SMS, and webhook notifications for AI agents with built-in idempotency and provider abstraction.
Structured log aggregation and session-correlated traces for full observability into AI agent workloads in production.
AI agents are fundamentally different from chatbots. Learn what makes an agent agentic and why this distinction matters for enterprise adoption.
A step-by-step tutorial for building and deploying your first AI agent with FireFoundry in under 30 minutes.
The gap between a working demo and a production system is vast. Understand the hidden challenges that kill most AI projects.
Deep dive into how the Entity Graph provides zero-code persistence for business objects and enables agent memory across sessions.
Reliable, Observable, Operational: the three pillars every production AI system needs. A framework for enterprise AI success.
How AI agents transform customer service from scripted responses to intelligent, context-aware conversations that resolve issues.
When AI fails in production, debugging is notoriously difficult. Learn how full observability transforms incident response.
Announcing Ensemble Groups, a new feature that enables multiple LLMs to collaborate on complex reasoning tasks.
Tutorial: Build an AI agent that extracts information from documents, classifies content, and routes to appropriate workflows.
Build a complete AI-powered document processing pipeline with human-in-the-loop review using FireFoundry's SDK.
Introducing FireIQ, an AI-powered conversational BI solution that lets you query databases in plain English.
PullChain pipelines, hierarchical task pools, and dependency-aware scheduling — the async primitives powering FireFoundry's concurrent agent workflows.
Part 1 of 3: How DAS gives agents governed access to 12+ database backends, semantic views that reshape data without touching source systems, and a dictionary that turns raw schemas into business knowledge.
Part 2 of 3: Ontology-driven business domain modeling, process rules that encode tribal knowledge, and AST-based queries that eliminate SQL injection by construction.
Part 3 of 3: Row-level security, scratch pad working memory, named entity recognition with fuzzy matching, and cross-database federation.
Why most AI agent demos never make it to production, and what infrastructure you actually need to bridge the gap between prototype and production-grade system.
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