From intent to governed execution
The governed execution layer for trusted enterprise AI action
avirat.ai helps businesses move AI from pilots, prompts, and isolated agents into governed execution across real systems, roles, policies, approvals, costs, and evidence.
Governance · Execution · Assurance
Let's understand your priorities
Tell us a little about yourself. We will route your request to the right person.
Market Shift
AI agents are joining the workforce.
As AI begins to act across systems, trust can no longer depend on intent alone. It has to be built into the way work is executed.
Harjeet Singh Gulati
Group Chair & CEO, Cerebrent
AI is no longer just drafting, summarizing, classifying, or searching. It is beginning to plan, decide, coordinate, trigger workflows, call tools, update systems, and complete work.
That changes the enterprise question
AI adoption
88%
of organizations now report regular AI use in at least one business function.
Agent experimentation
39%
are already experimenting with AI agents.
Execution is scaling
23%
are scaling agentic AI somewhere in the enterprise.
The Problem
Ungoverned AI execution.
As agents move into real workflows, enterprises face a new risk: AI work that spreads faster than control, visibility, and accountability.
Agent
Sprawl
Multiple agents emerge across teams without shared standards, ownership, or oversight.
Shadow
AI agents
Teams deploy agents outside approved systems, creating hidden risk and fragmented control.
Conflicting
autonomous agents
Agents act on different instructions, policies, or data sources, creating inconsistent outcomes.
Untraceable
business decisions
Actions are taken without clear records of what happened, why, and under whose authority.
Siloed platform
governance
Controls stay locked inside individual tools instead of governing work across systems.
Lack of
observability
Leaders cannot see agent activity, exceptions, costs, approvals, or outcomes in one place.
Enterprises have AI tools. They do not yet have enough control over AI work.
The gap is widening between where AI is being added and where control actually exists. Agents are entering everyday software, but most enterprises still lack a common way to govern the work those agents perform.
33%
Market acceleration
of enterprise software applications will include agentic AI by 2028 up from less than 1% in 2024.
40%
Production risk
of agentic AI projects will be cancelled by the end of 2027 due to cost, unclear value, or inadequate risk controls.
The next enterprise AI gap is not adoption. It is governed execution; the layer that makes agentic work controlled, auditable, cost-aware, and safe to run.
Trust Infrastructure
What production AI needs before it can act.
Once AI starts taking action, trust cannot depend on intent. It needs infrastructure that controls context, authority, execution, failure, cost, and evidence while work is being done.
Grounding
AI must act on approved, current, relevant context.
Continuity of Context
Workflows need memory across systems, people, agents, policies, and time.
Agent Orchestration
Execution needs sequencing, state, fault tolerance, and escalation.
Authority
Every action needs explicit limits on access, change, approvals, and spend.
Evidence
Every decision, tool call, approval, exception, and outcome must be defensible.
Managing Failure
Failures need rollback, compensation, human escalation, or a defined terminal state.
Economics
Cost must be controlled by step, workflow, model, tool, and outcome.
Deloitte reports that only 21% of surveyed enterprises have mature governance in place for agentic AI. Yet 74% expect to use AI agents at least moderately by 2027.
Introducing avirat.ai
avirat.ai is an operating layer for governed AI execution.
avirat.ai gives businesses the operating layer to run agentic workflows across existing systems with governance, execution, and assurance built in. It does not replace CRMs, ERPs, service desks, finance systems, or approval tools. It governs the work that moves between them.
The result → AI agents can act with clear authority, runtime controls, cost visibility, and evidence for every outcome.
The enterprise AI reset
What Governed AI Execution Must Get Right.
Governance | Control
Sets the boundaries for what AI can access, decide, trigger, approve, escalate, or spend.
Execution | Orchestration
Coordinates agents, tools, workflows, systems, approvals, and exceptions while work is being done.
Assurance | Accountability
Captures the evidence needed to review, trust, audit, improve, and scale AI work.
Platform Capabilities
The platform for governed AI execution.
avirat.ai brings together the capabilities needed to move AI work from experimentation to production.
Intent-to-Workflow Creation
Collaborative
Workflow Spaces
Enterprise System
Integrations
Multi-agent
Orchestration
Workflow
Economics
Trace View &
Audit Evidence
Runtime Policy
Enforcement
- Platform
- Workflow
- Agent
- Tool
Industry Solutions
Purpose-built intelligence for complex enterprise environments.
Start with one workflow.
Scale the pattern.
avirat.ai helps teams prove value with focused industry workflows, then reuse the same control, orchestration, and evidence patterns across systems, teams, and business units.
Insurance
- Claims review and investigation
- Underwriting support
- Fraud and exception routing
Pharma &
Healthcare
- Regulatory monitoring
- Quality audits
- Documentation compliance
Finance
- Risk assessment
- Regulatory compliance
- Automated reporting
Manufacturing
Supply Chain
- Operations optimization
- Supply chain intelligence
- Quality control
Construction
& Infrastructure
- Compliance monitoring
- Vendor management
- Project monitoring and reporting
Enterprise
Operations
- Support workflows
- GRC and audit workflows
- IT and operational escalation
Media &
Publishing
- Rights and usage review
- Content approval workflows
- Editorial operations and compliance
Ready for the Enterprise
Designed for the operational realities of enterprise AI.
Enterprise AI needs more than a working agent. It needs permissions, policies, approvals, integrations, deployment control, and evidence built into execution from day one. avirat.ai is designed for the realities of enterprise AI adoption.
Security & Compliance
Permission-aware execution, role-based access, approvals, and reviewable evidence.
Governance
Policies, audit trails, exception handling, and human-in-the-loop controls built into execution.
Operating Controls
Usage visibility, execution limits, workflow guardrails, retry controls, and model/tool routing.
Integration
Connectivity across systems, tools, APIs, data sources, models, and existing workflows.
Deployment Flexibility
SaaS, private hosted, on-prem, or air-gapped deployment options.