IT & Infrastructure context
- ITSM
- Monitoring
- Cloud Platforms
- Identity & Access
- Device Management
Operations
Turn Operations Into an Agentic Operating System
Production-grade AI agents that connect systems, workflows, data, and operational knowledge to help teams reduce manual work, respond faster, prevent issues, and scale execution without adding headcount at the same pace.
Production-grade · Human-controlled · Built on your existing stack
One intelligence layer across your operations stack
Shared operational context for every agent, workflow, and decision. Your existing systems remain the source of truth. The AI layer connects the signals, workflows, rules, and actions around them.
Business Operations context
- ERP
- Procurement
- Supply Chain
- Project Management
- Service Operations
Communication context
- Team Messaging
- Meetings
- Calendar
- Ticketing
Knowledge context
- Runbooks
- Policies
- SOPs
- Architecture Documentation
- Incident History
- Vendor Documentation
From Reactive Work to Proactive Operations
AI that helps operations detect earlier, coordinate faster, and execute more consistently.
Operational Visibility
Bring together signals across systems, teams, tickets, and processes into one current operating view.
- Bring together signals across systems, teams, tickets, and processes
- Create one current operating view
Incident & Exception Management
Detect unusual events, prioritize what matters, identify likely causes, and prepare the next action.
- Detect unusual events
- Prioritize what matters
- Identify likely causes
- Prepare the next action
Workflow Automation
Automate repetitive operational work across tickets, requests, approvals, documentation, and recurring procedures.
- Automate repetitive work across tickets and requests
- Automate approvals and documentation
- Automate recurring procedures
Service Delivery
Coordinate people, systems, vendors, and tasks around defined SLAs and customer outcomes.
- Coordinate people, systems, vendors, and tasks around defined SLAs
- Coordinate work around customer outcomes
Process Intelligence
Identify bottlenecks, repeated failure points, unnecessary handoffs, and opportunities for automation.
- Identify bottlenecks and repeated failure points
- Identify unnecessary handoffs and opportunities for automation
Continuous Improvement
Use operational outcomes and human feedback to improve workflows, runbooks, and agent behavior over time.
- Use operational outcomes and human feedback
- Improve workflows, runbooks, and agent behavior over time
Representative workflow
Operational Visibility
- Bring together signals across systems, teams, tickets, and processes
- Create one current operating view
The Operations operating layer
Core Agent Architecture
A connected operating layer across your operations function.
Connected Systems / Integrations
Shared operational context
IT & Infrastructure
- ITSM
- Monitoring
- Cloud Infrastructure
- Identity & Access
- Device Management
Business Operations
- ERP
- Procurement
- Supply Chain
- Project Management
- Service Management
Communication
- Team Messaging
- Meetings
- Calendar
- Ticketing
Knowledge & Control
- Runbooks
- SOPs
- Policies
- Architecture Documentation
- Incident History
- Vendor Knowledge
Representative examples we build for operations teams
Core Agent Architecture
A connected operating layer across your operations function.
Monitoring & Intelligence Agents
1
Operational Intelligence Agent
Combines operational signals and business context into a decision-ready view.
2
Incident Detection Agent
Identifies anomalies, recurring patterns, and operational risks early.
3
Root Cause Intelligence Agent
Combines operational evidence to help isolate likely causes faster.
Service & Workflow Agents
4
Service Triage Agent
Classifies, prioritizes, and routes requests with the needed information.
5
Resolution Agent
Executes approved remediation, prepares fixes, or triggers playbooks.
6
Workflow Orchestration Agent
Coordinates multi-step processes across systems, teams, approvals, and vendors.
7
SLA & Escalation Agent
Tracks service commitments and escalates exceptions before deadlines are missed.
Knowledge & Improvement Agents
8
Runbook Agent
Turns procedures and historical resolutions into executable workflows.
9
Knowledge Update Agent
Captures incident and project changes in updated operational documentation.
10
Process Improvement Agent
Analyzes recurring work and failure patterns to identify automation opportunities.
IT 2.0 Agents
11
Infrastructure Optimization Agent
Surfaces infrastructure inefficiencies, recurring costs, and optimization opportunities.
12
Agentic IT Operations Agent
Coordinates monitoring, triage, remediation, documentation, and escalation across IT.
Shared Operations Platform
Workflow orchestration
Coordinates agents, sequences, state, exceptions, and actions.
Shared operations context
Makes systems, processes, incidents, owners, and operational knowledge available across workflows.
Prompting & reasoning
Applies approved logic, operating procedures, and decision criteria.
Testing & QA
Evaluates accuracy, relevance, completeness, usefulness, and alignment with operating procedures.
Human review
Defines where people approve, edit, override, or make the final decision.
Rollout controls
Controls permissions, automation levels, write-back, quality thresholds, and expansion.
Actions can run automatically, request review, or pause for an exception based on policy and available evidence.
What each agent does12 full descriptions
Monitoring & Intelligence Agents3 agents
- 1
Operational Intelligence Agent
Combines system signals, service data, tickets, and business context into one decision-ready view.
- 2
Incident Detection Agent
Identifies anomalies, recurring patterns, and potential operational risks before they become larger problems.
- 3
Root Cause Intelligence Agent
Brings together logs, recent changes, incident history, dependencies, and known issues to help teams isolate likely causes faster.
Service & Workflow Agents4 agents
- 4
Service Triage Agent
Classifies incoming requests, prioritizes them, gathers missing information, and routes them to the right workflow or owner.
- 5
Resolution Agent
Executes approved remediation steps, prepares recommended fixes, or triggers defined operational playbooks.
- 6
Workflow Orchestration Agent
Coordinates multi-step operational processes across systems, teams, approvals, and external vendors.
- 7
SLA & Escalation Agent
Tracks service commitments, identifies risk of breach, and escalates exceptions before deadlines are missed.
Knowledge & Improvement Agents3 agents
- 8
Runbook Agent
Turns operational procedures and historical resolutions into guided, executable workflows.
- 9
Knowledge Update Agent
Captures what changed during incidents and projects and turns it into updated operational documentation.
- 10
Process Improvement Agent
Analyzes recurring work, handoffs, delays, and failure patterns to identify the next automation opportunity.
IT 2.0 Agents2 agents
- 11
Infrastructure Optimization Agent
Surfaces infrastructure inefficiencies, recurring operational costs, and opportunities for automation or consolidation.
- 12
Agentic IT Operations Agent
Coordinates monitoring, triage, remediation, documentation, and escalation across the IT environment.
Primary Users & Outcomes
Operations users and outcomes
Users
- CIO / CTO
- IT Leadership
- Infrastructure Teams
- Service Operations
- Security Operations
- Business Operations
- COO
- Operations Managers
Outcomes
- Faster response
- Lower operating cost
- Higher capacity
- Fewer recurring issues
- Better service levels
- Proactive operations
- Stronger operational knowledge
IT 2.0
Move from reactive IT to agentic operations.
Traditional IT spends a large share of its capacity reacting: Tickets arrive. People investigate. Teams coordinate. Issues are resolved. Documentation is updated later. IT 2.0 changes the operating model. Agents continuously monitor, interpret, prepare, execute, and escalate inside clearly defined boundaries. The result is a shift from reactive IT to proactive, increasingly automated operations.
Detect
Identify issues, anomalies, and recurring patterns earlier.
Understand
Bring together the relevant technical and business context.
Act
Execute approved operational tasks and playbooks automatically.
Escalate
Bring people in where judgment, risk, or ambiguity requires them.
Learn
Capture what happened and improve the next response.
90-Day Agentic Transformation
Build measurable operational impact in one quarter.
For selected organizations, we structure the transformation as a focused 90-day program.
Stabilize
Map the environment, identify operational friction, and strengthen the core infrastructure and control model.
Automate
Deploy agents into high-frequency operational workflows where manual work can be safely reduced.
Measure
Track time returned, cost reduction, response speed, quality, and operational impact.
Reinvest
Use the capacity and savings created by automation to fund the next stage of the transformation.
Scale
Expand the agentic operating model across additional IT and business operations workflows.
Let the Transformation Help Fund Itself
Efficiency becomes fuel for the next stage.
One of the most powerful ideas in the IT 2.0 model is that transformation should create capacity early. Reduce repetitive work. Return hours to the team. Lower operational cost. Improve response and resolution times. Then reinvest part of that value into the next wave of automation. Optimize → Save → Reinvest → Expand That changes AI transformation from a pure cost center into a compounding operating model.
From Tickets to Autonomous Workflows
Move beyond AI assistants into coordinated execution.
The biggest operational gains come when AI moves past answering questions and begins participating directly in the workflow.
Signal arrives
A ticket, alert, request, or operational event enters the system.
Context is assembled
The agent gathers the relevant data, system state, history, policy, and dependencies.
The workflow is selected
Rules and reasoning determine the appropriate path.
Routine work executes
Approved actions happen automatically where the risk profile allows it.
Exceptions escalate
People receive the context, evidence, and recommended next action.
Outcome is recorded
The resolution becomes part of the future operating context.
Scale the Knowledge of Your Best Operators
Turn operational experience into reusable intelligence.
Your best operators possess years of experience, pattern recognition, and judgment that traditional systems struggle to capture. They know which alerts matter, how failures are connected, which actions are safe, and how to prevent problems before they escalate. We transform that expertise into shared operational intelligence, intelligent runbooks, and AI agent workflows, enabling the entire organization to make better decisions, resolve issues faster, and continuously improve. Expert knowledge → shared intelligence → agentic execution → stronger operations
Primary Users & Outcomes
Reduce the time between signal, understanding, and action.
Users CIO / CTO IT Leadership Infrastructure Teams Service Operations Security Operations Business Operations COO Operations Managers
Faster response
Reduce the time between signal, understanding, and action.
Lower operating cost
Automate repetitive operational work and reduce manual coordination.
Higher capacity
Let teams support more work without growing headcount at the same rate.
Fewer recurring issues
Use incident history and process intelligence to eliminate repeated failure patterns.
Better service levels
Track, prioritize, and escalate work more consistently.
Proactive operations
Identify risks and issues before they become critical.
Stronger operational knowledge
Turn tribal knowledge into reusable systems.
Where Could Your Operations Team Turn More Signals Into Faster Action?
Bring us one high-value operational workflow.
IT support. Incident response. Service delivery. Infrastructure operations. Procurement. Workflow coordination. Knowledge management. Process automation. We’ll map the workflow, connect the relevant systems and knowledge, and define the first production AI agents needed to create measurable operational impact.
The Operations Operating Layer
See how your AI agents work together.
Connected systems. Shared operational context. Coordinated agents. Clear human control.
Operations workspace
Shared contextDecision view
Context before the next step
One operating context
Systems, incidents, processes, owners, dependencies, and priorities remain connected.
One workflow layer
Agents understand what should happen next, who owns it, and what rules or approvals apply.
One knowledge layer
Runbooks, procedures, architecture, policies, and historical incidents become reusable operational intelligence.
One exception model
Routine work can be automated while ambiguous or high-risk cases are escalated to people.
One learning loop
Every incident, resolution, approval, and outcome improves the next cycle.
How We Work
Start with one workflow. Build the operating layer to scale.
01 
Start
Choose one high-value operational process. Map the systems, data, runbooks, owners, dependencies, exception paths, and success criteria.
02 
Expand
Connect shared operational context and activate additional agents on top of the same foundation.
03 
Run
Measure outcomes, refine the workflows through real operational feedback, and increase automation as quality and trust are proven.
Human + Machine, One Intelligence.
AI handles repeatable execution. People own the exceptions.
AI agents monitor, classify, coordinate, prepare, and execute. People handle ambiguity, high-impact decisions, exceptions, and strategic priorities.
- Existing systems remain the source of truth
- High-risk actions stay human-controlled
- Routine work can become increasingly automated
- Every important action can remain traceable
- Operational knowledge improves over time
Evidence sets the route
Automation is conditional. The action, its sources, and the team’s policy determine what happens next.
Grounding checkApproved context & evidence
Check that the source is relevant, current, and sufficient for this action.
Source Policy Confidence
Auto
Within policy and grounded in approved context.
Proceed within the agreed boundaryReview
A person is required for this action or audience.
Route to the right ownerEscalate
Evidence is missing, conflicting, or outside policy.
Pause and surface the exceptionInsufficient source? Pause the action, surface what is missing, and send the case for resolution.
Traceable outcomeEvidence → route → decision → result
EvidenceAction pathOwnerOutcome
A system design example. Review is required only when the action or policy calls for it; source failures follow an exception path.
Build an Agentic Operations Function
What would change if your operations could act before the issue became a problem?
Tell us the operational workflow you want to transform. We’ll map the opportunity, connect the relevant systems and knowledge, and build the first production AI workflow around measurable business impact.