Strattum provides a cloud‑native context infrastructure that links an enterprise’s disparate data sources—CRM, ERP, help desk, databases, documents—to AI agents such as Claude, ChatGPT, Copilot, and others. By ingesting, cataloguing, and governing data, it delivers structured, up‑to‑date knowledge via its Model Context Protocol, enabling agents to make more accurate decisions while remaining LGPD‑compliant.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises often store critical information across multiple siloed systems such as CRM, ERP, help desks, databases, and document repositories. AI agents that rely on large language models cannot access this fragmented data, leading to inaccurate or incomplete responses and decisions.
Solution
Strattum delivers a cloud‑native context infrastructure that aggregates, governs, and continuously updates an organization’s disparate data sources into unified knowledge graphs and skill sets. Through its open Model Context Protocol (MCP), the platform exposes this structured context to any LLM—Claude, ChatGPT, Copilot, Gemini, or custom models—without requiring model retraining. The service runs entirely within the customer’s own cloud environment (AWS, Azure, GCP, OCI, or on‑prem), ensuring data residency and compliance with regulations such as LGPD. By providing real‑time, governed context, Strattum enables AI agents to make more accurate, enterprise‑specific decisions while preserving flexibility to switch models as needed.
Target Audience
Primary customers are large enterprises and mid‑market organizations that deploy AI assistants or LLM‑based applications and need secure, governed access to internal data across multiple systems.
Features
- Automated ingestion, cataloging, and transformation of data from CRM, ERP, help desk, databases, documents, and arbitrary sources
- Governance layer that enforces data quality, lineage, and compliance policies
- Memory Graph, Knowledge, and Skills modules that expose structured context via the open Model Context Protocol
- Compatibility with any LLM that supports MCP, eliminating vendor lock‑in and integration rewrites
- Full deployment within the customer’s cloud infrastructure (BYOC), ensuring data never leaves the organization
- Observability and evaluation tools for monitoring context quality and performance in production