Modern lending stacks already make thousands of decisions every day — but turning those decisions into timely action across systems is where most friction still sits. Business rules engines define policy, underwriting systems score borrowers, and operations teams interpret outcomes across tools.  
 
 
Sentinel AI sits at the centre of this decision layer, bringing clarity to how risk decisions are made. That intelligence is no longer confined to a single interface — it can now be accessed by other systems across your lending stack and used where decisions need to be acted on. We’ve built secure hooks that let your existing systems talk directly to Sentinel AI. With them, you can: 

• Let your LOS react to Sentinel AI’s underwriting decisions automatically 

• Let tech teams add custom logic for special cases—without changing the core system 

• Automate parts of your lending workflow instead of handling them manually 

• Build new use-cases faster, without heavy engineering 

So, you can ask plain-language questions or trigger actions through your existing systems—your LOS, internal copilots, ops dashboards, or even ChatGPT—without new dashboards or workflows to learn. 

Here’s a possible conversation, for example: 

You can extend the same workflow to approvals, drift, error summaries, portfolio changes, and partner funnels. 

You could also ask things like: 

• How did approvals trend this week? 

• Is our MSME scorecard behaving as expected? 

• Show me anything unusual in yesterday’s decisions. 

• What changed in Partner A’s funnel this morning? 
   

  Responses arrive as structured, actionable insights powered entirely by Sentinel AI. 

What is MCP and how does Sentinel AI make this innovation possible?  

To enable this new conversational interface, Sentinel AI uses the Model Context Protocol (MCP) -- an open standard that allows AI assistants to talk to existing business systems securely and consistently. 

You can think of MCP as a shared ‘handshake’ that lets Sentinel AI and your AI assistant communicate without custom integrations or complex engineering work. Here’s how it works in Sentinel AI: 

• Your AI assistant becomes the ‘host’ 
  The host is simply the place where you type your question — LOS, internal risk tools, AI copilots, or even ChatGPT. The host doesn’t store Sentinel AI data; it only knows how to ask Sentinel AI for what you need.  
   

• The assistant uses an MCP ‘client’ to speak Sentinel AI’s language. 
  A small component sits inside the host that understands how to communicate with Sentinel via MCP. Think of it as a translator that ensures that the questions you ask are structured correctly, and Sentinel AI’s answers return in a clean, predictable format that’s immediately meaningful and actionable. This keeps everything smooth and reduces any miscommunication between systems. 

  
  

• Sentinel AI becomes the MCP ‘server’ 
  This is where the intelligence lives. Sentinel AI exposes specific, permission-controlled functions --— like fetching model performance, summarising logs, comparing scorecards, or highlighting drift. The assistant accesses only what it is allowed to, and Sentinel AI handles all the heavy lifting behind the scenes. 
  Together, these three pieces allow your everyday questions to reach Sentinel AI instantly and safely, and come back with clear, actionable insights. 

  
  

What this means for your teams 
 
Instant clarity, anywhere you work 
If you’re analysing a trend or reviewing performance, you can simply ask: “What caused yesterday’s dip?” 

Your assistant will return a structured summary directly from Sentinel AI: key rule contributions, partner-level differences, changes in patterns, and any drift indicators. You get the full picture without switching tools. 

Smoother investigations during high-volume periods  
When something changes unexpectedly, having information at your fingertips matters. 
Now you can ask: 

• Show me the latest policy errors. 

• Were any features behaving differently today? 

• Did we see any anomalies this morning in the funnel? 

The assistant pulls the relevant Sentinel AI insights and explains them in plain language. 
You stay in the flow and move quickly from questioning to understanding. 

Effortless model and policy exploration 
Testing ideas becomes far more intuitive. Ask questions and give commands like: 

• Compare the challenger policy with the current scorecard 

• Run the new rule on last week’s data and analyse performance 

• What’s the expected uplift if we adjust this threshold? 

Sentinel AI runs the evaluations; your assistant presents the results clearly. 
This helps teams explore improvements confidently without slowing down day-to-day work. 

Faster onboarding of new team members 
New analysts or PMs can learn Sentinel AI through simple questions like: 

• What scorecards do we use for personal loans? 

• What rules drive income estimation? 

• How did we perform last month? 

This shortens the learning curve and helps new team members understand your risk stack immediately. 

Sentinel AI, now within reach in one question 
This new conversational interface doesn’t replace the depth of Sentinel AI, it amplifies it. 

 
You still have the full platform for deep dives and structured workflows. But now, you also have a lighter, faster option for everyday clarity. Sentinel AI can now help you optimise risk, improve workflows and build deeper understanding – not just in the interface but pretty much wherever you need it.  

Try it today.