Thanks to Temporal, Fred makes document ingestion as reliable as microservices — with automatic retries, fine-grained observability, and custom pipelines for push or pull ingestion. A true game-changer for AI apps.
July 20, 2025 in architecture, ops, orchestration by Alban Capitant, Simon Cariou, Florian Muller and Dimitri Tombroff5 minutes
Instead of relying on fragile regex scripts or complex linters, Fred uses AI to catch mismatches between backend code and Helm deployments. This makes deployment safer and helps teams move faster.
July 14, 2025 in devops, configuration-management, ai-review by Dimitri Tombroff4 minutes
Fred now supports agentic access to tabular data like CSV and Excel through a new DuckDB-based backend and the Tessa agent. Explore how this works and what it unlocks.
July 11, 2025 in data, agents by Thomas Hedan4 minutes
We use GPT-4 internally to automate Python code reviews and ensure compliance with Fred's backend development standards. Learn how our AI review tool works and why it matters.
June 20, 2025 in devops, configuration-management, ai-review by Dimitri Tombroff5 minutes
Fred can now observe power and energy usage in Kubernetes via MCP and Kepler. This post walks through the setup and shows example visualizations and insights.
June 2, 2025 in kubernetes, observability by Simon Cariou3 minutes
Fred is now capable of serving and consuming components over the Model Context Protocol (MCP). Discover how this unlocks new architectures and makes Fred a live testbed for building interoperable AI agents.
May 19, 2025 in architecture, mcp, open-source by Simon Cariou, Alban Capitant and Dimitri Tombroff6 minutes
Fred is now composed of three modular components: a React UI, an agentic backend using LangGraph, and a knowledge-centric backend for document processing. Learn how it all fits together.
May 7, 2025 in architecture, announcement by Kevin Denis, Dorian Finel-Bacha, Julien Ornat, Fabien Le-Solliec and Dimitri Tombroff4 minutes
Running Fred with a local Ollama server
March 7, 2025 in guidance by Emanuel-Todor Hascau-Dumitrelea and Dimitri Tombroff2 minutes
Large Language Models (LLMs) are revolutionizing enterprise automation and decision-making, but evaluating their effectiveness with proprietary data poses unique challenges. This post explores these complexities and their critical importance for successful enterprise adoption.
January 12, 2025 in architecture by Tanguy Jouannic, Dimitri Tombroff and Dorian Finel-Bacha16 minutes
How to chat with Fred's team of expert. A practical introduction.
December 7, 2024 in guidance by Lorenzo Gerardi2 minutes