Agentic AI Development
Build multi-step AI agents that plan, reason, and act across tools, APIs, and user workflows. Production-grade agentic systems with real tool orchestration, retrieval, evaluation, and memory.
Multi-agent systems, tool-using agents, RAG pipelines, agentic memory, agent evaluation frameworks, sandboxed execution environments, and co-pilot interfaces. Ensembles of specialized agents that run independently, aggregate results, and make system-level decisions.
Orchestration with LangGraph, OpenAI Agents SDK, Anthropic Agent SDK, and Agno. Interfaces built with ChatKit and custom React components. Retrieval via vector databases and RAG pipelines. Memory patterns from Mem0 and Zep. Evaluation through tracing, scoring, and automated testing. Infrastructure on Vercel, Supabase, AWS, and Postgres.
Most studios advise on AI. MetaModern builds it. We ship working agent systems, not strategy decks. We architect tool orchestration, RAG, and memory — not just ChatGPT wrappers. Everything is production-grade with tracing and guardrails.
The agentic AI market hit $7.29B in 2025, projected $9.14B in 2026. Gartner says 40% of enterprise apps will feature AI agents by end of 2026. Implementation services are growing 240% YoY. The demand is massive — the supply of people who can actually build this stuff is tiny.
More services.
From zero to shipped
