Custom AI-native solutions
Built to be used by people, chatbots, agents, workflows and analytics, from the first day.
The reactive body of knowledge. We build it around your domain, your rules and your identity: one model of how your business works, which notices when reality changes and acts on it, with five ways in from the day it ships.
one model · five ways in
- people
- chatbots
- agents
- workflows
- analytics
The definition
AI-native · adjective
AI-native means every capability is built to be used by five kinds of consumer from the start, not retrofitted for one.
01
People
Staff, customers and partners, through interfaces.
gets
Screens and notifications that already know the context, because they read the same model as everything else.
02
AI chatbots
Conversational surfaces that answer from the same model of the business.
gets
Answers grounded in your entities and rules, with the source of each, instead of whatever text sat nearest the question.
03
Background AI agents
Processes that notice, decide and act without being asked.
gets
Standing expectations to watch, thresholds to act on, and the role to hand over to when they should not act alone.
04
Automation workflows
Deterministic pipelines and integrations.
gets
Events with a stable shape and rules they can call, so a decision is encoded once instead of copied into every pipeline.
05
Data and analytics systems
BI, forecasting and reporting that read the same truth.
gets
A feed of the same entities and events, so the dashboard and the chatbot cannot disagree about what a customer is.
One body of knowledge, five ways in.
An idea modelled once becomes all five surfaces, so nothing is re-explained to each.
Tailored
Tailored means three things, and each one is written down.
A custom system is only custom where it encodes something true of your organization and of no other. These are the three places that happens.
- 01Your domain
- The entities, events and relationships your business runs on: the customer, the contract, the shipment, the incident, and which system of record owns each one.
- you can openA versioned domain model, diffed and reviewed like code.
- 02Your rules
- Policies, thresholds, approvals and compliance dates, encoded, versioned and testable. A rule changes in one place and every consumer follows it.
- you can openRules as code with tests, not paragraphs in a prompt.
- 03Your identity
- Your voice, your brand, and the roles that must act. The system speaks as you and routes to your people by role, not to a shared inbox.
- you can openA voice guide and a role map the system reads, not a style memo.
From idea to organism
It develops. It is not installed.
The same developmental arc as the rest of our work, followed from a single idea. Each stage ends in something you can open, and the time boxes are the ones we commit to for every engagement. How the engagement runs.
012-week audit
Conception
The idea, stated as the decisions it must improve and the people who make them. If the decision cannot be named, we do not build.
deliverable
A decision brief.
022-week audit
Body plan
The domain model, and an inventory of every rule the idea depends on, read from your systems rather than your slides.
deliverable
A wiring map and a rule inventory.
03by week 6
Nervous system
An event spine connects the systems of record, and the first signal travels end to end on your real systems.
deliverable
One working path in production.
04continuous
Myelination
Use decides what gets hardened. The paths that carry the most value get tests, monitoring and speed; the rest stay light.
deliverable
Hardened paths, and the usage data that chose them.
Myelin is laid down along the axons that carry activity.
05retained
Maturity
All five consumers are live on the same model, and the system reports its own prediction error, so you can see whether it is getting better.
deliverable
Five surfaces and a monthly error report.
Mature cortex forwards the prediction error, not the raw input.
Day one
What exists the day it goes live.
Day one is the day the first slice reaches production, 6 weeks from the start. On that day each of these exists, and each one can be opened, run or read.
The domain model
Your entities, events and relationships, in a repository, diffed on every change.
The rule set, as code
Every rule the first slice depends on, with tests that fail when a rule is broken.
One end-to-end signal
A real event on your systems, noticed, decided on, and handed to the role that must act.
A chatbot surface
Answering from the domain model, with the source of each answer.
An analytics feed
The same entities and events, readable by the BI tools you already run.
An error report
What the system expected, what happened, and the gap between the two.
Honest proof
No logos. A method you can check.
LEAPNODE is new. We are not going to show you logos we do not have. What we can show you is the method, the citations behind it, and a fixed-scope audit small enough that you can judge us on evidence instead of on a deck.
Questions
Asked before you have to.
Is this a chatbot project?
No. A chatbot is one of the five consumers. It answers from the same model the agents, workflows and dashboards read, and that shared model is the work; the chat window is one surface on it.
Do we have to replace our systems?
No. Your systems of record stay where they are and stay the owners of their data. We model what they hold and connect them with an event spine.
Which AI models do you use?
Whichever the job needs, and as few as it can get away with. Small models next to the data do most of the work; the expensive call stays rare and is budgeted.
What does it cost?
We do not publish prices. Every engagement starts with the 2-week audit, which is fixed in scope and fee, and you keep the wiring map whether or not you continue.
How does this relate to the reactive body of knowledge?
It is the same architecture, described by who uses it. The home page explains what the system is. This page explains what it serves.
Start