AI-Ready Backend
Connect AI agents to your backend with the permissions you set
We build MCP servers and clean APIs on top of your systems, so AI agents can read your data and take actions in your tools, only where you allow it.
Tell us the use case. We'll show you what it takes to connect it to your backend.
Sound familiar?
- 01
Leadership wants AI features, but your data is locked inside systems with no clean API.
- 02
You built a chatbot demo, and it can't do anything useful because it can't reach your company's data.
- 03
You're worried about what an AI agent could do with full database access.
- 04
Every integration with Salesforce or another CRM is custom code that breaks after updates.
- 05
Your codebase is too inconsistent for AI coding assistants to extend reliably.
The cost of waiting
Waiting has a cost here too
Competitors are already connecting agents to their sales, support, and operations data. Each month your systems stay closed to AI, those features remain a slide in a planning deck.
Our approach
How we approach it
MCP servers with access control
Model Context Protocol (MCP) is an open standard for connecting AI agents to software. An MCP server describes your system's data and actions in a form any compatible agent can discover and use. We build MCP servers on your backend with defined permissions, so each agent sees and does only what you approve.
A working MVP, fast
Our backends are structured for this from the start, so we can build an AI MVP on top of them quickly. It could be an agent connected to your services, your CRM (Salesforce, for example), and the other tools your team uses. You see a working result on your own data before deciding where to invest.
A codebase AI can extend
Every part of the codebase is documented and follows one consistent structure, so AI coding tools can extend it correctly. Simpler future changes can be made with AI assistance, and the architecture leaves room for your developers to build the complex ones.
Before and after
Before
After
- Before: AI demos with no access to company data
- After: Agents working with your data and tools
- Before: "Give the agent database access" as the only option
- After: Agents limited to the actions you approve
- Before: Custom CRM integrations that break
- After: Integrations through a documented, standard interface
- Before: AI coding tools that produce code that doesn't fit
- After: A documented structure AI tools follow
Deliverables
What you get
- An AI-readiness review of your backend and data
- An MCP server for your core services, with access controls
- Connections to AI agents and external tools such as Salesforce
- A working AI MVP built on your own data
- Documentation written for both developers and AI coding tools
FAQ
Questions teams ask before hiring us
01Is it safe to let an AI agent into our systems?
Agents connect through an MCP server we build with explicit permissions. They can only read and do what you approve, and actions can be logged for review.
02Which AI models and agents does this work with?
MCP is an open standard, so any compatible agent or AI client can use it.
Next step
Have an AI use case in mind?
Tell us about it, and we'll show you what it takes to connect it to your backend.