Connect Your Business Systems to Your Own AI
We wire your ERPs, databases, and business applications to the AI tools your team already uses — ChatGPT, Claude, Azure OpenAI, or custom agents — via Model Context Protocol (MCP), function calling, or standard APIs. Tenant-scoped, authenticated, audited.
Service Overview
The most valuable AI in your organisation is often not the AI you built — it's the AI your team already uses every day. ChatGPT for research. Claude for analysis. Cursor for code. Azure OpenAI in a custom agent. What's usually missing is the wiring: how do those tools securely query your CRM, invoice records, HR data, or talent pool — without exposing everything, and without every team member copy-pasting between windows? BlueAura designs and delivers AI integration — the connective tissue between your business systems and the AI that consumes them. We use Model Context Protocol (MCP) where it fits, standard APIs and function calling where that's the right shape, and always with tenant scoping, authentication, and audit trail by design.
Business Problems We Solve
Your team's AI tools can't see your data
Employees use ChatGPT or Claude for productivity, but those tools have no visibility into your CRM, ERP, HRMS, or line-of-business apps.
Copy-pasting between AI and business systems
Staff paste queries into AI, then paste answers back into records. The productivity gain is smaller than it should be — and audit-invisible.
Data exposure risk from ad-hoc AI use
Employees paste sensitive data into consumer AI tools because no structured, secure connection to enterprise AI exists.
AI vendors that lock you into their agent
Off-the-shelf AI tools force you to use their agent, not the one your team already trusts — restricting choice and locking your data behind their platform.
Custom AI that only serves one use case
Bespoke AI agents built for one workflow, then re-built from scratch for the next. MCP servers become reusable across every AI client that speaks the protocol.
What BlueAura Provides
Technologies We Use
Related Products
Our own products that demonstrate this service in action.
How We Engage
MCP server build
Design and deliver a Model Context Protocol server that securely exposes one or more of your business systems to any MCP-capable AI client (Claude, ChatGPT, Cursor). Typical: 4–8 weeks.
AI integration Proof of Concept
Fixed-scope POC: pick one business system and one AI client, prove the mechanism against real data. Typical: 3–4 weeks.
Custom AI agent build
Build a domain-specific AI agent on Azure OpenAI, with the tools, data, and prompts scoped to your business — deployed inside your tenant.
AI integration discovery
A 2–3 week discovery to identify the highest-value AI integration use cases across your business, and design the target architecture.
Managed AI integration operations
Ongoing managed service for your AI integration infrastructure — monitoring, incident response, audit review, and continuous improvement.
Frequently Asked Questions
What is Model Context Protocol (MCP)?+
MCP is an open protocol (launched by Anthropic, adopted by OpenAI, Microsoft, Cursor, and others) that lets AI clients like ChatGPT or Claude securely call tools and read data from external systems. Instead of building a one-off integration for every AI client, you build one MCP server and any MCP-capable client can use it.
Why should we connect AI to our business systems this way?+
Because the AI tools your team already uses every day become dramatically more useful when they can query your actual data — safely, with proper permissions and audit. It's the difference between generic AI answers and AI that knows your business.
Is this secure? Doesn't the AI see everything?+
No. MCP servers enforce tenant scoping and per-user permissions. The AI can only query the data your access-control policies allow, exactly like any other user of your business systems. Every query is logged for audit review.
Do we have to use ChatGPT or Claude specifically?+
No. MCP-capable clients today include Claude, ChatGPT, Cursor, and a growing list of others. Non-MCP integrations (OpenAI function calling, custom agents) also work — we pick the right mechanism per use case.
How is this different from just building a chatbot?+
A chatbot is a UI wrapper around an AI. AI integration is the plumbing that lets any AI client — a chatbot, a custom agent, an IDE like Cursor, or your team's existing ChatGPT — reach your business data. Chatbots are one consumer of the plumbing; MCP servers serve many.
Can you integrate with our existing enterprise systems?+
Yes. We integrate with SAP, Oracle, Microsoft Dynamics, custom LOB applications, SQL databases, SharePoint, and REST APIs. The MCP server is the abstraction layer; the underlying data can be almost anywhere.
What kinds of use cases are the best fit?+
Common early wins: querying a talent pool ("who are my best available Angular developers?"), Q&A over enterprise documents ("summarise this quarter's contract renewals"), workflow triggers ("open a ticket in ServiceNow for anything flagged high-risk"), and internal knowledge assistants (HR policies, engineering runbooks, sales playbooks).
How much does MCP integration cost?+
A typical MCP integration Proof of Concept for one business system starts around RM15,000, fixed-scope. Full production MCP servers scale with the number of systems exposed and the complexity of the access-control model. We provide a business case as part of discovery.
Do you have this running in production today?+
Yes. Our Talio talent management product ships with an MCP connector so recruiters can query the pool from their own ChatGPT or Claude. We also deliver custom MCP integrations for enterprise clients — spanning SAP, custom LOB apps, and SharePoint.
Let's discuss your ai integration & mcp project
Free consultation to scope your needs and recommend the right approach — products, custom build, or both.