Kappal Platform Stack
RudderAI
AI that turns data into decisions.
RudderAI is a governed decision-intelligence layer. It reads across PropelOS and your existing systems and surfaces what needs attention next, with reasoning your auditors can review. Every output runs through role-based access, full audit and guardrails, in the cloud, hybrid or fully on-premise.
Decision intelligence, governed
Turn data into decisions, not guesswork
Insight is the point, governance is the harness. RudderAI reads across PropelOS and your existing systems, and turns what they already know into signals your teams can act on, inside boundaries your security team approves.
Decision Intelligence
Reads across PropelOS and your existing systems and flags what needs attention next, from stock-outs to pricing gaps, with reasoning your auditors can review.
The model suggests, the system decides
A deterministic harness around every model call: timeouts, retries, circuit breakers and fallbacks. A hallucination becomes a logged event, not a business decision.
No shadow AI
Every agent and tool your teams use is approved, metered and visible to your security team. What is not provisioned in RudderAI does not touch your data.
Your data never leaves
Deploy in your region, your VPC or fully on-premise. Nothing trains on your data, and nothing crosses your boundary without permission.
What ships in RudderAI
Decision signals, agents and automations, every one governed, auditable and deployable in your boundary.
AI Analytics
Signals with an audit trailReads across PropelOS and your existing systems and surfaces what to do next: stock-outs, cash-flow pressure, churn risk and pricing gaps, with reasoning your auditors can review.
Agent Orchestration
Workflow first agentsBuild agents and copilots with deterministic workflows, human-in-the-loop steps and versioned prompts your team can review.
Plugin Architecture
Connect any systemSeamless connectors to your legacy databases and modern SaaS, so agents act on the data you already own.
Guardrails and Access Control
Boundaries enforcedRole-based access on data and actions, content filters and scope limits that keep every model inside its lane.
Audit and Observability
Fully traceableEvery prompt, response, cost and decision is logged and searchable, ready for compliance review.
Model-Agnostic Runtime
No vendor lock-inOpen models, fine-tunes or vendor APIs behind one interface. Swap models without touching your agents.
From pilot to governed scale
RudderAI rolls out in stages, so your security team stays in control at every step.
Discover
We map your data, your access boundaries and the use cases that justify AI. You approve the scope first.
Pilot
Teams run agents in a sandboxed environment, with guardrails on from day one.
Govern
Role-based access, audit and policies are configured before anything reaches production.
Run
Monitor cost, quality and safety. Expand to new use cases from a governed baseline.
Kappal's own security controls, encryption and data handling are documented. Ask for our security and architecture pack.
Enterprise outcomes, honest economics
No license taxes on what you are not running yet, proof before commitment, and terms written down before code. Cost scales with adoption, not ambition.
Pay for what you run
Platform fees track the modules and volume you actually use. No per-seat tax on capabilities you have not switched on.
Prove it first
A live proof of concept on our infrastructure in days, with your data. You see real outcomes before you approve a wider rollout.
Staged and reversible
Roll out module by module with a review gate at each step. Every phase is measurable, and every phase can be taken back.
Terms before code
SLAs, data processing agreements and commercial terms are agreed and written down before production work starts.
Tell us your scale on the first call and we will give you a range to plan against.
Ready to turn data into decisions?
Bring us a use case where your data should be making the call. We will show you the architecture and a pilot plan, with your security team in the room.