Make AI agents reliable with code-aware RAG, practical vector DBs, and ML-security alerts

Make AI agents reliable with code-aware RAG, practical vector DBs, and ML-security alerts targets a $8.0B = 200,000 professional ML/AI teams/orgs x $40K ACV total addressable market with medium saturation and a year-over-year growth rate of 30%+ = rapid adoption of vector DBs, RAG and agent frameworks across industries.

Key trends driving demand: LLM-driven agents -- agents are shifting more product surface-area to retrieval and orchestration, increasing demand for reliable RAG.; Managed vector DB maturity -- production-ready vector DBs reduce infra friction and lower time-to-production for retrieval systems.; ML observability & security -- post-deployment model incidents and regulatory attention push teams to monitor models, inputs, and infra.; Open-source acceleration -- toolkits like LangChain/LlamaIndex speed prototyping, raising expectations for integrated managed solutions..