Factorial CTO details production AI agent architecture handling 25-product SaaS complexity
Building reliable AI agents for complex enterprise SaaS requires a 'harness' pattern with dynamic skill routing, deterministic tool execution, and analytical databases (DuckDB) to overcome…
DuckDB enables analytical SQL execution inside AI agent loops to bypass LLM context limits
Embedding an in-process analytical database (DuckDB) allows AI agents to perform complex joins and aggregations on large datasets without overflowing context windows, solving the token cost…
Tool design and evaluation frameworks matter more than model selection for production AI agents
The speaker argues that investing in tool harnesses, evaluation pipelines, and deterministic data layers (like DuckDB) delivers more reliable AI agents than chasing incremental model improv…
Multi-tenant SaaS companies can deploy AI agents safely via permission-aware tool proxies and usage-based pricing
Factorial's architecture shows how to deploy AI agents in regulated multi-tenant environments: enforce data isolation at the API layer, use deterministic tool proxies instead of raw model p…