Connect your AI systems to the data and tools your business actually runs on.
THE CHALLENGE
An AI assistant that cannot see your systems is a very expensive search box. The value appears when a model can read the right record, call the right internal API and take the right action, safely and with an audit trail. Getting there means building the connective tissue between models and enterprise systems that were never designed with AI in mind.
OUR APPROACH
Bespoke Model Context Protocol servers that connect your AI systems to enterprise data sources, internal APIs, and business workflows at scale.
We understand your business requirements, existing systems and operational challenges.
We design an AI approach that fits your workflows, data and technology environment.
We turn the solution into a production-ready system that can be measured and improved.
WHAT'S INCLUDED
A practical engagement designed around your business requirements, technical environment and desired outcomes.
Identify the systems, data sources and workflows that need to be connected.
Design and develop custom MCP servers for your AI systems.
Implement authentication, authorization and scoped permissions.
Define the tools and resources exposed to AI systems.
Introduce controls for usage, performance and cost.
Maintain visibility into what AI systems access and do.
Provide a testing harness and controlled sandbox environment.
Deploy the MCP integration and provide supporting documentation.
HOW WE WORK
A structured process keeps every engagement focused, transparent and aligned with business outcomes.
Talk to our teamAudit your data, tech stack, and AI readiness
Architect the solution with security-first principles
Build iteratively with continuous stakeholder input
Ship to production with full observability stack
Monitor, fine-tune, and scale for sustained ROI
EXPECTED OUTCOMES
We focus on outcomes that create practical value for your organization, rather than implementing technology for its own sake.
TECHNOLOGY & PLATFORMS
We choose technologies based on your requirements, infrastructure, scalability and long-term maintainability.
LLM
LLM
Open Source
Open Source
LLM
Framework
Framework
Platform
ML
Cloud
Cloud
Cloud
Infra
Infra
Vector DB
FAQ
Everything you need to know before starting an engagement with Nitiverk.
Ask our teamMCP provides a structured way for AI systems to interact with external tools, resources and data sources.
The integration depends on the APIs, data sources and business systems available in your environment.
Authentication, authorization and scoped permissions are incorporated into the integration design.
The integration can be designed around your existing authentication and identity environment.
Deployment can be designed around your infrastructure and hosting requirements.
Versioning, testing and documentation are considered as part of the integration lifecycle.
EXPLORE MORE
End-to-end delivery of production-grade AI products: from architecture design and model selection through to deployment, monitoring, and iteration.
Deploy powerful open-source language models within your private infrastructure. Full data sovereignty, air-gapped environments, and compliance-ready.
AWS, Azure, GCP — we architect cloud-agnostic solutions that avoid vendor lock-in and optimize cost.
Whether you are exploring a new AI opportunity or scaling an existing system, let's discuss how Nitiverk can help you move from strategy to production.