Codalio for Energy

Governed AI software development for energy & utilities

For oil & gas, utilities and critical infrastructure. On-premises, air-gapped or Canadian-hosted.

Describe what your operation needs in plain English. Codalio turns it into a living plan, a build path against your existing systems, and tested, compliance-checked code. Your engineers approve every change before it ships.

Full traceability

Every change traces to a requirement, a test and a compliance check.

Brownfield-first

Plans against your legacy apps, data and operational technology / information technology (OT/IT) boundaries.

Deploy where data stays

Canadian-hosted, on-premises or air-gapped — where your data must stay.

Scope an energy POV Watch the 2-min demo

Built in Canada

Why energy is different

Why AI adoption in oil & gas and utilities needs more than a chatbot

Energy and critical-infrastructure teams carry a higher bar for security, regulatory compliance, access control and operational continuity. In the physical world, a confident wrong answer isn’t an inconvenience; it’s an operational event. So energy has been slow to adopt AI, for good reasons. That changes once the controls are in place. You need evidence of what was requested, what changed, how it was tested, whether it complied with policy, and who approved it.

Legacy systems no one fully documents

Critical logic lives in decades-old applications and in the heads of people close to retirement. Systems record what happened. The why behind past engineering decisions is often lost.

Siloed data across departments

Operations, maintenance, engineering and finance each hold part of the picture, so nobody has one view to make decisions from.

Compliance and audit pressure

Every system change has to stand up to regulators, auditors and your own change-management board. AI makes generating work almost free, but verifying it is now the bottleneck.

Data residency and sovereignty

Sensitive operational data can’t flow to whichever public AI tool a developer prefers.

Energy doesn’t need another chatbot. It needs AI that can reliably take part in engineering work.

The shift

ChatGPT or Claude directly vs a governed AI software development life cycle

Models supply capability. Codalio makes it usable in a regulated environment.

USING A FOUNDATION MODEL DIRECTLY

Teams assemble prompts, context, AI helpers and hand-offs themselves
Large, general prompts get unreliable as the codebase grows
Polished demos look alike; what happens behind the chat window is opaque
Governance evidence has to be designed and enforced outside the tool
Requirements, edge cases and the reasons behind decisions end up scattered across chats and tickets

CODALIO

A role-based AI workflow is generated for each work item, with shared context
Specialised AI workers operate in deliberately narrow contexts: plan, code, test, debug, review, compliance
AI orchestrates your trusted, deterministic tools and existing systems; it doesn’t impersonate them
Built-in traceability: requirement → code → test → compliance check → approved pull request, so verification is part of the flow, not an afterthought
A living specification keeps requirements, decisions and edge cases as durable company intellectual property
AI workers get scoped, role-based permissions, the same way a new employee earns authority step by step

We’re not competing with OpenAI or Anthropic. Codalio is the governed engineering layer around the models you choose, and your domain experts stay the deciders.

Two capabilities

Legacy application modernization using AI, in both directions

Build forward. Understand backward.

Requirements → Code

State an objective in plain English, such as a predictive-maintenance app for field assets. Codalio produces the product plan, technical plan, implementation plan and production code you own, then opens a pull request for your engineer.

Code → Requirements

Point Codalio at a legacy codebase and it reverse-engineers it into readable documentation and a living specification. That’s the starting point for modernization, stack migration, disaster recovery and vendor independence. It starts from requirements, not tribal knowledge.

The factory floor

The factory floor: nine stations, human gates

Plan, develop, write tests, run tests, debug, review, compliance, commit, merge. The orchestration is configured automatically. Your engineer reviews and merges; Codalio never ships on its own.

Plan
Architecture & implementation plan vs. your existing systems
Develop
Proven patterns + AI for the code that differentiates you
Write Tests
Coverage built from spec acceptance criteria
Run Tests
Full suite executed, results captured
Debug
Failures diagnosed & fixed in-loop
Review
Quality, security & architecture checks
Compliance
Validated against your regulatory rules & standards
Commit
PR opens with full end-to-end traceability
Merge
Your engineer reviews, approves & ships

Granular role-based permissions
Compliance validated against your regulatory rules and standards
Human approval before release
Brownfield-first planning

See how it works

Two short walkthroughs of AI requirements-to-code and code-to-documentation, one in each direction.

Requirements to Code

Plain-English objective → product plan, technical plan, tested code and a pull request.

Code to Requirements

Legacy codebase → readable living specification, the starting point for modernization.

Deployment and sovereignty

On-premise, air-gapped and sovereign AI deployment

Deploy where your data has to stay.

All deployment models are available: Codalio cloud, Canadian-hosted with open-source models, your own cloud tenancy, on-premises inside your network, or fully air-gapped with locally hosted models. Codalio is built in Canada, and your code is always exportable. There’s no lock-in to a runtime only we can host.

Detailed security posture, integration patterns and a security FAQ are shared under NDA during POV scoping.

Fast Start

Start with a 60-day AI pilot for your energy team

A proof of value your procurement team will approve.

Bounded scope. Clear exit criteria. NDA and master license signed up front, so a successful pilot rolls straight into deployment without restarting legal. One team, one workflow, chosen with you. Architecture and security reviews at named milestones. A written ROI model and expansion plan at day 60.

Full Fast Start details

$10K for the 60-day pilotCAD unless stated otherwise

DAYS 0–10

Frame and align

Workflow selection, data and integration access, named success metrics. Architecture and security checkpoints scheduled with your team.

DAYS 10–45

Guided build, in your environment

Specification, implementation, and operational baseline delivered inside Codalio. Reviews at named milestones — no surprises at day 60.

DAYS 45–60

Measured outcomes and expansion plan

Outcomes evaluated against the metrics you set. ROI model and a written expansion plan delivered to your sponsor.

Predictive maintenance appLegacy app → living specificationUnified view over siloed operational dataRegulatory reporting workflow

Scope an energy POV

FAQ

Questions energy and utility IT leaders ask

Teams use AI to document legacy applications, generate requirements and tests, and build new internal tools faster. Codalio runs that as a governed pipeline: living plan, specialised AI workers, tests, compliance gates and a pull request your engineers approve.

Yes. Code → Requirements reverse-engineers legacy code into readable documentation and a living specification, then Requirements → Code rebuilds against it within your existing architecture. Nothing changes until your team approves.

Codalio can. Deployment options include on-premises inside your network, fully air-gapped with locally hosted models, your own cloud tenancy, or Canadian hosting. Exact topologies for a pilot are scoped under NDA.

It doesn’t have to. Canadian-hosted, private-cloud, on-premises and air-gapped deployments keep data where your residency rules require.

Every change traces to a requirement, a test result, a compliance check and a named human approver. That’s the change record auditors ask for. Your compliance team decides how each system is classified. We do not claim NERC CIP certification.

No. Codalio is the orchestration and delivery layer around the models you choose, with human gates on architecture, security and release.

Energy adopts AI more slowly than other industries for good reason: the cost of being wrong is physical. Once the controls exist (verified outputs, scoped permissions, human sign-off), adoption can move fast.

$10K for 60 days: one team, one workflow, named success metrics and a written ROI model. See Enterprise → Fast Start.

Yes. It’s in your repository, exportable, with no runtime lock-in.

Next step

Bring us the objective you’ve been trying to scope for months.

We’ll show you working software against it, inside your standards.

Scope an energy POV Book a demo