Kalpita PromptOps · Autonomous DevOps Product
Describe the pipeline you want. PromptOps builds it, runs it and heals its own failures — with you approving what matters.
PromptOps is an autonomous DevOps product for Azure that builds CI/CD pipelines from natural language and resolves failures automatically in under 60 seconds.
Turn a plain-English request into a governed Azure pipeline that fixes itself.
The problem
Hand-written YAML is complex and brittle. Pipelines fail often, releases wait on a handful of specialist DevOps engineers, mean time to repair runs high, and configuration drifts across environments.
The work that was supposed to accelerate delivery now slows it down — and every new service multiplies the problem.
What it does
Engineers describe what they need in plain English; PromptOps generates and validates the pipeline, then runs it. When a run fails, AI agents read the logs and resolve the issue automatically.
Day-to-day operations happen through a conversational interface, and governance plus human approval guard every change — speed that never bypasses compliance.

Capabilities
Intent in, governed automation out — six capabilities that remove the YAML bottleneck without removing control.
Plain-English requests become production-ready Azure CI/CD pipelines as validated YAML and ARM definitions.
AI agents detect and resolve failures in under 60 seconds, so a broken run heals itself instead of stalling the release.
Run builds, releases and day-to-day operations through chat rather than consoles and one-off scripts.
Automated validation enforces compliance on every change, so consistency is a property of the system rather than a review habit.
Engineers sign off on sensitive actions before they reach production — automation proposes, people decide.
Live pipeline health, drift detection and proactive recommendations across every environment on one dashboard.
From a sentence to a governed, self-healing pipeline in six steps.
Describe the pipeline or operation you want in plain English.
PromptOps generates the YAML or ARM definition and validates it against governance rules.
Azure DevOps executes the pipeline while PromptOps monitors the run in real time.
On failure, AI agents analyse the logs and apply a fix automatically — usually within 60 seconds.
Sensitive changes route to a human for approval before they reach production.
Live dashboards surface pipeline health, configuration drift and recommendations.
Against hand-written, manually operated pipelines: intent in, governed automation out.
| Capability | Kalpita PromptOps | Traditional Azure DevOps |
|---|---|---|
| Pipeline creation | Plain-English prompt → validated pipeline | Hand-written YAML by specialists |
| Failure handling | Self-healing in under 60 seconds | Manual triage; high MTTR |
| Operations | Conversational and chat-based | Console- and script-driven |
| Consistency | Generated and validated — around 0% YAML errors | Drift across environments |
| Specialist dependence | Reduced — teams self-serve | Bottlenecked on DevOps engineers |
| Governance | Automated validation plus approvals | Manual reviews, uneven enforcement |
Who it's for

PromptOps is built on Azure AI Foundry and Azure OpenAI for intelligence, Azure Functions for orchestration, Azure DevOps for execution, and Microsoft Entra ID for identity and governance. YAML and ARM templates are generated and validated automatically, and validation layers enforce compliance on every change.
Proof, not promises
95%Faster Setup
Onboarding a service
Removing YAML authoring collapses the time between a new service and its first governed pipeline.
Under 60Seconds
Self-healing
AI agents read the failure logs, identify the cause and apply a fix — without waking an engineer.
~0%YAML Errors
Generated + validated
Every definition is produced and checked by the same governed path, so configuration drift stops recurring.
~$120K+Saved
Modelled annual effort
Reduced manual pipeline authoring and failure triage, modelled across a cloud-native delivery organisation.
Higher Reliability
Across environments
Consistent, validated definitions mean deployments behave the same in every environment they reach.

Book a 30-minute demo and watch a plain-English request become a governed, self-healing Azure pipeline.
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