Analyze and understand how your business runs
K-AI lets teams ask operational questions in plain language and get answers grounded in your process model and your actual data. Every answer is traceable back to the exact data and model elements that produced it.
AI lacks process context
Most AI tools see tables or documents. They do not know how work moves across the business, which relationships are trusted, which exceptions are normal, or which rules the team has validated.
Without that context, answers are generated from schemas or heuristics with no traceable link to actual operations. Technical teams have to verify manually. The business cannot confidently act.
Get answers grounded in how work actually happens
K-AI operates on the process model your team has already defined and validated in Process Graph. It does not reconstruct operational logic on the fly or guess at relationships. It uses what is already there.
Answers in minutes, not analyst-days
Every answer is traceable to your process model and source data
The model gets smarter with use — every gap K-AI surfaces becomes a reviewable improvement
From business question to trusted answer
Ask
K-AI is designed for questions that cross systems and teams:
- Why are these orders delayed?
- Which cases are at risk of breaching SLA?
- Where is rework increasing?
Business users ask in plain language. K-AI maps the question to the relevant parts of the process model and the data behind it.
Investigate
A dashboard tells you a metric is bad. K-AI helps you understand why.
K-AI traces where a delay starts, which systems are involved, and what the evidence shows. The cause often sits across several places — a supplier issue, a stock gap, an approval delay — and K-AI follows the thread across all of them.
Output
A useful answer should not die in a chat thread. When K-AI surfaces a pattern or a risk, that finding can become:
- A dashboard view
- A monitoring rule
- An alert
The same process model that supported the answer also supports the output built from it.
Inspect
Every response is one of four types:
| Response type | When it happens |
|---|---|
| Grounded answer | Enough evidence exists in the model and data |
| Clarifying question | The question has multiple valid interpretations |
| Declared gap | Required data or model structure is missing |
| Proposed model update | The answer exists in raw data but needs a model change to be reusable |
K-AI does not guess. If the answer cannot be grounded in your process model and data, it says so.
Answers your teams can verify
K-AI is designed to be checked. Technical teams can inspect the data used, the model elements applied, the assumptions made, and the gaps found.
The business gets useful answers. Technical teams get the evidence they need to trust, challenge, or improve them. Invented evidence is not allowed. Unsupported answers are rejected by the system.
Runs inside your environment
K-AI runs on top of Process Graph and follows the same deployment model. Queries execute directly in your data platform using SQL or Spark. Your data stays in your environment.
Data
Operational data remains in your environment.
Execution
Queries run in your data platform using SQL or Spark.
Control
Existing access and permissions stay in place.
Costs
Full visibility and control over infrastructure and token costs.
See how K-AI turns a question into a trusted answer
We run K-AI against a real process model and walk through how it reasons step by step. You see every query, every model element used, and every assumption made.
Book a demo