AIONIQ Build makes your Data and Product AI-ready. AIONIQ Operate runs and governs the AI in production.
| Agent | Model | Calls / 24h | P95 | Success | Drift | $ / day | Status |
|---|---|---|---|---|---|---|---|
| PO Approval | Claude | 412k | 780ms | 99.2% | Stable | $1,840 | Running |
| Claims Triage | Claude | 286k | 910ms | 98.7% | Stable | $920 | Running |
| Onboarding Copilot | Claude | 198k | 640ms | 99.5% | Stable | $410 | Running |
| Fraud Sentinel | Claude | 154k | 1.1s | 97.9% | Watch | $560 | Running |
| Data Assistant | Claude | 121k | 520ms | 99.8% | Stable | $210 | Running |
| NOC Runbook | Claude | 73k | 880ms | 98.4% | Stable | $270 | Paused |
79% of enterprises have deployed AI agents. Only 11% run them in production. The reason is rarely the model or the budget. It is that one team builds the AI and a different team has to run it, and the work breaks at the handover.
Your data, your applications, and the way the AI is run are what carry it into production, and none of that comes with a model subscription.
It was built to fill dashboards. Agents need it live, governed, and ready to act on, which is a higher bar.
Most prove the idea. Few carry the governance and operating model that production needs.
AIONIQ does two things. Build makes your data and applications AI-ready and puts agents into production. Operate runs them. Both come from one company, so you deal with one team from the first build to live operations.
AIONIQ runs on an open foundation Parkar owns and operates end to end, deployed in your environment. You never touch the plumbing. What Parkar adds is the know-how to run it as one working system, sharpened across hundreds of engagements so each project moves faster than the last.
Deployed in your own cloud across Azure, AWS, and GCP, and certified on Databricks and Snowflake. No third-party plumbing for you to license or manage.
Accelerators handle the parts of a build that usually drag, so you spend weeks where others spend months.
Your data, your outcomes, and your audit trail stay yours. Nothing locks you in.
Build works across your data and your applications. Every project starts with a quick readiness check that sets the plan, then accelerators do the heavy lifting.
Build opens with the AI Readiness Diagnostic, a scored check that shows where you stand and gives you a prioritised first wave of work to tackle.
Most enterprises do not need a rebuild to start using AI. They need what they already run made usable by agents. Weeks to AI-ready on legacy. Months to weeks on a modernisation.
Operate runs your AI in production and keeps your existing IT operations steady underneath it. The same team that built the AI runs it.
Running agents is different from running servers. Models drift over time, and an agent can take an action you need to trace and approve. Costs move with every token you spend. Operate watches all of it, so your AI keeps working long after launch day.
Model inventory across the enterprise, risk scoring, shadow-AI detection, and compliance reporting against the EU AI Act, NIST, and ISO 42001.
A managed identity for every agent, least-privilege access, automated secret rotation, and agent behaviour monitoring.
We run the governance end to end, and the audit trail is yours. A drop in agent accuracy is treated as an incident, with someone accountable for fixing it.
Legacy lending monolith causing weeks-long compliance cycles and failing at peak. Decomposed to cloud-native microservices on AWS with a strangler-fig migration.
18 months of stalled PoCs taken to a governed PO-approval agent on SAP and Workday. Policy-as-code, hard human approval, full audit trail.
Free, ten questions. See where you stand before you spend on another tool or pilot.
Five days, fixed fee. You get a readiness scorecard and a prioritised first wave of work, scoping both Build and Operate. The output is yours whether you continue or not.
Accelerators make your estate AI-ready and put governed agents in production.
The same team runs it, for the long term, on top of the operations you already trust.
The Diagnostic shows you where you stand. The Assess Session sets the plan. Then we build it and run it, on one platform.
Most enterprises do not need a rebuild to start using AI. They need the right path for each application, and one partner accountable for the whole thing.