Autonomous agents fail when disconnected from live business context or exposed to unvetted API tools. We build and harden private Model Context Protocol servers directly inside your cloud perimeter, connecting deep agents to SAP, TOTVS, and SQL databases under zero-trust governance.
Public SaaS connectors and brittle API scripts create catastrophic security holes and runtime hallucinations.
Public SaaS connectors require routing sensitive database credentials and customer records through third-party multi-tenant clouds. CISOs and risk committees reject external data transit on regulatory grounds.
Stochastic models guess unmapped columns, foreign keys, and status codes on complex ERPs. When an agent calls an unhardened tool, malformed payloads fail silently or trigger destructive database rollbacks.
Without granular role-based bounds, an agent granted write access can mutate inventory tables, trigger duplicate vendor disbursements, or bypass enterprise authorization tiers without supervision.
Generic REST webhooks provide no standard audit trail for AI actions. In the event of an operational anomaly, engineering teams cannot trace which prompt triggered which tool call or verify parameter provenance.
Production-ready Model Context Protocol infrastructure deployed inside your sovereign environment.
Containerized, high-throughput Model Context Protocol server written in Python or TypeScript, deployed directly inside your VPC on AWS, Azure, GCP, or on-premise Kubernetes clusters with zero external dependencies.
Strict runtime input validation and typed JSON schemas. Prevents agent payload distortion before execution hits backend stored procedures, transactional tables, or microservice gateways.
Zero-trust access policies tied directly to corporate identity providers like Okta, Microsoft Entra ID, or Google Workspace. Agents execute tools under strict ephemeral scoped permissions with customer KMS encryption.
Native OpenTelemetry instrumentation exporting structured execution traces. Logs tool invocations, parameter hashes, execution latency, and return states to your existing Datadog, CloudWatch, or Splunk stacks.
A structured context engineering protocol from legacy discovery to verified production deployment.
Network topology review, VPC isolation setup, and staging credential provisioning.
Extracting ERP schema tables and converting business rules into deterministic contracts.
Coding the private MCP server with rigid input validators and prompt injection guards.
Connecting Claude, Cursor, Copilot, or internal agents and executing regression suites.
Security audit sign-off, telemetry dashboard verification, and engineering runbook delivery.
The MCP Production Sprint is an intensive 12k USD enterprise engineering deployment. Qualified enterprises unlock our Performance Rebate: the fee is 100% credited toward your full production contract upon rollout.
Direct sponsorship from a C-level executive, such as the CTO, CIO, or CISO with architectural mandate.
Staging credentials, VPN perimeter access, or read replicas prepared before day one of the sprint.
An active enterprise roadmap deploying autonomous agents on core company workflows within 90 days.
Talk directly with our engineering team to review systems, evaluate perimeter constraints, and schedule deployment.
