Getting AI live is half the job. Keeping it running, watched and governed is the other half. Parkar runs the core IT you depend on and the AI on top, on one platform, with no handoff to a separate vendor. You get the outcomes. We run everything underneath.
Traditional managed services keep infrastructure healthy. AI adds a whole layer to watch, measure and govern that they were never built for. Here is the gap the leaders are closing.
Traditional support waits for the alert, then triages. Agents degrade quietly, and by the time a ticket is filed the damage is done.
Success measured in tickets closed and hours billed has nothing to say about whether the AI is still doing its job.
Infrastructure stays green while accuracy drifts. A 5% accuracy drop is a real incident, and most ops teams cannot see it.
Agents are non-human identities with real access. Perimeter security and human IAM were never designed for them.
Traditional MSPs have no AI muscle. AI-ops point tools have no enterprise grounding. The boundary between them is where programmes break.
You do not replace your IT operations. You extend them.
Everything the three pillars build lands here. AI Engineering, Data and Product all hand over to the same team, on the same platform.
One team across all four. The team that builds it runs it, so nothing has to be rebuilt in between.
The model is moving from waiting for tickets to preventing them, from billing hours to owning outcomes, and from a fixed vendor scope to a shared backlog. The bar for what operations means is rising.
Most vendors pick a side. Traditional MSPs have no AI muscle, and AI-ops tools have no enterprise grounding. We keep the core IT stable and govern, secure and orchestrate the AI workforce, with one team and no seam at the boundary.
One partner across the boundary where most programmes break. The core stays stable while the AI workforce is governed, secured and run.
Managed Operations is what you buy. AIONIQ is what we run it on. Every agent, pipeline, application and alert in one view, around the clock.
The runbooks came from eleven years of running production systems and now cover agents too, alongside AI inventory, risk scoring, audit reporting and an identity for every agent.
If an agent starts giving worse answers, that is an incident here, with a named owner and a response time we commit to.
Explore the AIONIQ platform →Three bundles aligned to your AI maturity. You start where you are and expand as you adopt. Each rung stands on its own and sets up the next.
A short Managed Operations Readiness assessment scores your operations against the AI-first
model and sets the phased path.
No commitment to continue.
Cloud infra ops, 24x7 service desk, application support and traditional security in place.
AI governance, shadow-AI detection, runtime protection and token-cost tracking.
Agent orchestration, LLMOps, GPU optimisation and vector operations.
Model refinement, cost optimisation, compliance updates and capability expansion.
You receive the cadence an ops team runs on. Daily incident and token-burn trackers, and monthly SLA, drift and AI-risk reviews. Start with predictable bundles and move to outcome-based as the AI layer matures.
Siloed IT and OT, mean time to acknowledge averaging 28 minutes, availability at 97.8%. Unified monitoring with a 24x7 NOC and automated runbooks.
A model inventory and shadow-AI detection stood up end to end, with a managed identity for every agent, all operated by Parkar.
Multi-agent workflows monitored with reasoning traces and retrieval-quality checks, and inference spend kept visible with token-level FinOps.
The AI Readiness Diagnostic scores where you stand and the road to AI-first operations. A few minutes, and you get a report and the right next step.