Corvana

Specialized AI for
critical infrastructure.

Corvana Labs builds specialized AI around your operational knowledge, systems, and people—tested on real tasks, with human review.

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Work with Corvana

The problem

Energy infrastructure wasn’t
built for generic AI.

Energy infrastructure runs on a mix of legacy systems and newer tools. The knowledge needed to complete a task is spread across asset records, project schedules, operating procedures, and the people who know how the work gets done.

General-purpose AI is a useful starting point for writing, search, and analysis. A utility workflow demands more: knowing which record applies, how equipment and activities depend on one another, what the procedure requires, and who needs to review the result.

Much of that understanding comes from experience. It shows up when someone resolves conflicting records, handles an exception, or coordinates work across teams. Giving AI access to documents captures only part of that context.

The challenge is turning knowledge across your systems, procedures, and people into AI that is grounded in your operations, tested on real tasks, and connected to the way work gets done.

An electrical substation with interconnected transformers, switchgear, and transmission equipment.

What we do

We build AI around your operations.

Corvana Labs builds specialized AI for energy, utilities, and critical infrastructure. We work with your experts to capture the decisions, dependencies, and exceptions behind a defined workflow, then connect the records, procedures, and systems it needs.

We adapt AI to that work and test realistic cases against agreed measures of quality and review effort. We then integrate the workflow into your existing tools with clear approval steps, training, and handover. Your team keeps responsibility for decisions, while quality, review time, and cost show how the workflow performs.

Our work brings together:

  • Operational context

    Capture the decisions, dependencies, and exceptions behind the work with the people who know it best.

  • Systems integration

    Connect records, procedures, and tools with the sources, versions, and access controls each workflow needs.

  • Custom AI models & validation

    Adapt models to your tasks. Test real cases and difficult exceptions against an agreed baseline for quality and review effort.

  • AI workflow implementation

    Build AI into existing processes with clear approvals, training, and handover. Measure quality, review time, and cost.

How Corvana works.

A construction crew reviewing plans beside the foundations of a three-dimensional substation.
DS-01Maintenance records
TX-01Operating procedure
SG-01Review examples
BESS-01Operating limits
From operational context to working AI

Map the work. Capture the context.

Scroll to explore
Construction crew reviewing a substation plan on a drawing table.

01 · Understand

Map decisions, dependencies, and exceptions with your practitioners.

A crane lowers the transformer while engineers assemble the substation.

02 · Build

Connect the right context and adapt AI to the defined task.

Engineers test the station using a portable test case and inspection leads.

03 · Validate

Test real cases against a baseline. Report limits and review effort.

Engineers connect the completed station, with energized cables and operating indicators.

04 · Implement

Integrate tools and approvals. Train your team and agree the handover.

Who we serve

Electric Utilities.
Solar Developers & Operators.

A power transformer and switching equipment at an electrical substation.

Electric Utilities

Connect asset, project, procurement, and customer work around your utility’s records.

Explore Electric Utilities

Evidence, not endorsements.

Case study 01 — Voice AI in customer operations. A Fortune 500 utility put a governed voice agent on its routine call types, with a human one utterance away. An anonymized account from the founding team’s work — figures representative. Representative impact ~$3M / yr run-rate Watch demo
Case study 02 — Sub-agents in workplan development.
Case study 03 — Predictive models in substations.

View other case studies
and see AI in action.

View other case studies

Our approach

How the work
comes together.

Four purple glass prisms ascending together

Solution 01

Operational Knowledge & Integration

Connect AI to the records and rules your work depends on.

Explore this solution
An illuminated public-power substation and transmission equipment at blue hour.

Connect approved procedures, asset records, work histories, and workflow knowledge so AI can retrieve relevant evidence within defined permissions.

  • Approved procedures and asset records
  • Work histories and workflow knowledge
  • Relevant evidence within defined permissions

Solution 02

Custom AI Models & Validation

Test AI on your work before you expand its use.

Explore this solution
Power transformers and switching equipment at an electrical substation.

Build expert-defined evaluation tasks and grading criteria to compare systems, identify failures, and measure improvements.

  • Expert-defined evaluation tasks
  • Grading criteria built around the work
  • System comparisons and failure analysis

Solution 03

AI Workflow Implementation

Build, integrate, and launch AI workflows alongside your team.

Explore this solution
Illustrative CorvanaOS workspace for context, workflows, and evaluation

We work alongside your operations and IT teams to build, integrate, test, and launch a defined AI workflow—with clear success measures, review steps, and an agreed handover.

CorvanaOSThe workspace supporting delivery and review.Corvana AgentCustom AI agents for utility workflows.
Illustrative CorvanaOS workspace for context, workflows, and evaluation

Corvana builds on the stack you already run — never locked to one vendor’s model.

Bring your tools.
Bring your AI.

Model-agnostic by design — Claude, Copilot, or ChatGPT, chosen per workflow and documented so the choice survives review. Every consequential action carries evidence and a named approver.

Logos and names are trademarks of their respective owners, shown to identify the tools utilities run — no affiliation or endorsement implied.

Security shaped for
regulated infrastructure.

Read more

Controlled access. Protected records. Accountable AI.

For energy and utilities, we scope security requirements with your team
around the systems, information, and work involved.

NERC CIP

Identify applicable bulk electric system requirements before connecting a workflow, including access boundaries, change controls, and vendor risk.

FERC · Grid security

Operational technology

Define the boundary between AI workflows and operational systems, with approved access, network separation, and human authorization.

NIST · OT security

Protected infrastructure data

Classify sensitive records and agree access, storage, retention, and permitted model-provider use. Apply CEII handling rules where relevant.

FERC · CEII

Enterprise assurance

Agree the evidence required for the delivery environment: supplier assessments, ISO 27001 certificates, and SOC 2 reports where procurement requires them.

ISO · Information security

AI governance

Define accountable owners, evaluate workflow risks, document human review, and retest material changes before release.

NIST · AI Risk Management

Applicability depends on the entity, jurisdiction, systems, and data in scope. These are engagement requirements to assess, not claims of Corvana certification.

Discuss your requirements

A few things to know.

What does Corvana Labs do?

Corvana Labs builds specialized AI for energy, utilities, and critical infrastructure. We help teams turn operational expertise into AI that can support a defined task, with clear measures of success and human review.

We start with your practitioners: map the workflow, capture decisions and exceptions, and connect the relevant records, procedures, and systems while preserving sources, versions, and access requirements.

We then adapt models to the task and evaluate realistic cases against agreed criteria for quality and review effort. When the workflow is ready, we integrate it into your existing tools, define approval steps, train your team, and agree the handover.

Our services cover Operational Context & Integration, Custom AI Models & Validation, and AI Workflow Implementation. Engagements can focus on one service or a sequence of services, with quality, review time, and cost measured against the agreed scope.

Can we engage you for just one solution?

Yes. You can engage us for operational knowledge and integration, AI evaluation and validation, or AI workflow implementation. Each engagement has its own scope and deliverables; moving to another stage is a separate decision.

Do we need to adopt CorvanaOS or Corvana Agent?

No. CorvanaOS is the workspace we are building to support delivery. Corvana Agent is customized for a defined workflow. Neither is a required software purchase: we scope the tools, access, and handover to the engagement and can work with your existing AI tools.

Can you evaluate another vendor’s agent?

Yes, where the system can be made available for a controlled evaluation. We agree the task set, information access, execution conditions, and scoring criteria so the comparison is useful.

What does operational knowledge and integration include?

We connect the records, procedures, and system data a workflow needs, preserve source versions and permissions, and check that AI retrieves the right evidence. Your team receives working connections, validation results, and named owners for keeping the information current.

Is the Corvana Utility Benchmark available today?

It is a research program in development. We are defining expert-reviewed cases and repeatable evaluation methods. Customer-specific evaluations are scoped separately; we do not present the program as a certification or an established industry standard.

How do you measure whether AI is useful?

We agree criteria for the complete workflow, including output quality, missed exceptions, unsupported conclusions, reviewer effort, and operating cost. Where the existing process lacks a baseline, establishing one is part of the scope.

What happens to our data?

We agree source access, processing, retention, model-provider handling, and permitted uses with your technical team. Reuse outside your engagement requires explicit permission.

What happens after deployment?

A defined review cadence, context maintenance, investigation of exceptions, and evaluation of proposed changes. The scope identifies who owns support, release decisions, and escalation.

How do we start?

Bring a recurring task, an existing AI system you want to assess, or a knowledge problem holding the work back. We will identify the appropriate offering, define the workflow and success criteria, and agree the next step.

Corvana

Voice AI

Customer operations

Read the walkthrough
  1. Scope routine outage, billing, and payment calls.
  2. Connect the agent to approved utility systems.
  3. Read the account, policy, and call context.
  4. Answer from the record and bring in a person when requested.
  5. Transfer the account context and full conversation.
  6. Keep sources, decisions, and actions together.
  7. Let the operations team review exceptions.
  8. Replay the workflow against source and escalation checks.
  9. Compare with a baseline. Engagement results: roughly 34% of in-scope calls resolved by voice AI.