Your app still works. The world moved on.
Adaptive AI makes an application you already run ready for the agentic-AI era. We wrap the APIs you have as skills an agent can call, then put agents and Insight.AI on top — so users get answers, automation and foresight inside the product they already use. No rebuild, and every phase is reversible.
ai-adaptive.ileaf.aiThe Adaptive AI service site — go and see it.Ask Lia about adaptive aiWhat this includes
- MCP skill layer
- Your existing endpoints exposed as Model Context Protocol tools, with scopes and limits per skill. Your core code is not rewritten.
- Agents that act
- Sequential and swarm agents that reason across those skills and complete whole tasks, not just answer questions.
- Insight.AI
- Plain-language questions against your own data, read-only by default, with prediction rather than another static report.
- Modular skills
- Voice, contract intelligence, forecasting, document understanding, anomaly alerts — added one at a time as your roadmap needs them.
- In-product experience
- The intelligence appears inside the interface your users already know, so there is nothing new for them to adopt.
- Approval gates
- Anything that writes or spends passes a human check until it has earned the right not to.
How we run it
Every phase ships something usable on its own, so you are never holding a half-finished system waiting on the next milestone.
Assess
We map your application, data and APIs — most of which, for existing clients, we built and still maintain.
Connect
Your services are wrapped behind an MCP-style skill layer, leaving the running system untouched.
Build
Agentic skills go in and Insight.AI stands up on your data, behind an approval gate.
Predict
Predictive intelligence layers over live operations — demand, churn, risk — measured against real outcomes.
Scale
Voice, automation and further skills are added on demand. Each phase shipped value on its own and can be rolled back.
What we build it with
- Model Context Protocol (MCP)
- LangGraph
- Python
- TypeScript
- Graph-RAG
- pgvector
- Neo4j
- Claude
- Open-weight models
- Redis
- Temporal
- OpenTelemetry
Questions we get asked
Do you have to rebuild our application?
No. Adaptive layers over what you already run. Your existing APIs are wrapped as skills an agent can call, so the core system keeps serving live users unchanged. That is the whole design premise — a rebuild would throw away years of accumulated business logic for no gain.
What if we did not originally build with iLeaf?
Adaptive still applies, it just starts with a longer assessment phase. If your system has APIs, they can be wrapped as skills. We begin read-only, produce a written map of your application and data, and scope the first skill from there.
How quickly do users notice a difference?
The first phase that reaches users is usually Insight.AI — plain-language questions against their own data — because it is read-only and therefore low risk. Automation that writes or spends follows once the approval gates and audit trail have been running long enough to trust.
Let’s talk about adaptive ai.
Tell us what you are running and what it needs to do next. We will tell you honestly whether we are the right team for it.