01
Choose the systems and data to use
Agree which company systems can be used, which records belong together, what outcomes matter and which software or AI will receive the result.
SOFTWARE ENGINEERING COMPANY / BUILT IN LIVERPOOL
Turn company data into the next best action.
KynticAI connects information from across a company, understands how it relates and what happened in what order, then recommends what to do next. Each recommendation includes the evidence behind it and how confident the system is.
Software built for real company systems, not an AI demo.
CONNECTIONS / OUTCOMES / RECOMMENDED ACTIONS
25+
FOUNDER YEARS
100+
COMMERCIAL PROJECTS
FTSE 250
DELIVERY EXPERIENCE
PRODUCTION
SYSTEMS, NOT DEMOS
Built in Liverpool. Sold worldwide.KynticAI Limited
A PRACTICAL PLACE TO START
Start with one valuable question.
You do not need to replace your existing systems or choose one AI model for everything. Start with a business question that matters, connect the information you already have and see whether a better understanding of that information leads to a better decision.
KynticAI products
One way of understanding company data. Different products for different jobs.
The products share the same basic approach. They connect information, keep track of what happened and in what order, remember where each fact came from and learn from previous outcomes. Other products then use that foundation for specific jobs.
Context Engine
Relationship intelligence family
Importance Engine
Importance and value family
Standalone product
Independent of either product family.
From company data to a useful action
The useful part is understanding what the data means before asking AI to explain it.
KynticAI first works out which information is connected, what happened in what order and what happened in similar situations before. It then returns a recommendation with the evidence, confidence and any warnings. AI can explain that result, but it does not have to invent the facts behind it.
01 · company data
Useful information is often spread everywhere.
Paul Madd / Paul Maddison
homepage visit
Context Engine page read
email submitted
previous similar journeys
02 · KynticAI connects it
The important facts are put together.
which records belong to the same person
what happened and in what order
which events led to good or bad outcomes
where the information came from and any warnings
recommended actions
03 · result
Recommended next action.
Email customer with X offer
75%
Offer design partner call
63%
Do not reply yet
83% no further contact
Learning from outcomes
What happened last time helps improve the next recommendation.
KynticAI does not only look at the current question. It also remembers what happened after similar events before: what succeeded, what failed, where people dropped out and which earlier events were most closely linked to the final result.
See how it learns →01
Events
02
Connections
03
Recommended actions
04
Outcomes
05
Better future rankings
Worked examples
See the information KynticAI used and the action it recommended.
These examples use synthetic data so the full process can be shown without exposing a real customer's information.
From first test to real use
Start with one useful question and prove it before doing more.
02
Keep company data under your control
Run the private KynticAI software inside the agreed customer controlled environment instead of moving operational data into the KynticAI cloud service.
03
Return a clear recommendation
Staff, company software and approved AI receive the recommended action together with the evidence, confidence and any warnings behind it.
04
Learn from what happened next
Record the outcome after each recommendation so similar situations can be ranked more accurately in future.