Enterprise AI transformation
Enterprise-wide AI transformation, deployed one connected function at a time.
Enterprise AI transformation, as Solonomous delivers it, is a phased programme: forward-deployed engineers connect your departments, the systems they already run and the data between them through governed AI agents, one function at a time. Agents take on defined work inside those systems; your people decide the exceptions and every regulated step.
What it is
A connected programme, not a collection of pilots.
Most organisations meet AI one tool at a time: a pilot in one team, an assistant in another, each with its own data and none connected to the systems where the work is recorded. A transformation programme starts from the other end. It maps how departments, processes, software and information connect, then puts agents to work along those connections, under the same security, audit and approval rules everywhere.
The aim is an organisation where agents carry more of the defined, repetitive work across functions, and people spend more of their time on the exceptions, the oversight and the next improvement. That is an aim, measured phase by phase, never a promised saving or a promised team size.
It is an active development direction for us: the methods, integration tooling and evaluation practice of our individual autonomous solutions, extended across departments. We describe it as a programme, phase by phase, and not as a completed deployment.
How it is phased
Five phases, each evaluated before the next.
Each phase ends in something running and measured. A phase is extended only where it is technically and commercially sound, and only when the people who own the work agree.
- 01
Discover
Map how departments, processes, software and data actually connect. Choose where agents can take defined work first, who owns each decision, which steps are regulated and how results will be measured. The output is a written roadmap, phase by phase, with an owner for each.
- 02
Connect systems and data
Integrate the systems the organisation already runs, from finance, procurement and operations to customer service and people systems, through scoped and logged access. Nothing is replaced wholesale: connectors work through the interfaces and permissions that already exist.
- 03
Governed agents, department by department
Agents are deployed one department at a time. Each has an identity, scoped permissions, a named owner and an audit trail, and each is evaluated against real cases with known answers before it touches live work.
- 04
The operating model
Agents run the defined work; people decide the exceptions. Each department keeps people with the context and the authority to decide what the agents hand over, and every regulated decision stays with the accountable person. Work that crosses departments runs only along paths the organisation has authorised.
- 05
Evaluation and oversight
Reliability and results are measured throughout: how often work goes to a person, how often a person overrules an agent, what each completed case costs. Automation is extended where those measures and the owners say it is ready, and paused or rolled back where they do not.
Offerings each phase draws on
- Readiness & Scoping SprintTwo weeks inside your systems; one workflow scoped in writing.
- Integration & Data OnboardingYour systems of record connected, your data modelled and governed.
- Evaluation & ObservabilityA golden set, a harness and dashboards, so a regression is caught before a user is.
- Managed OperationsWe keep running what we built, at a flat monthly fee, until you take it.
What you keep
Everything that runs is yours.
At the end of each phase, what was built stays with the organisation, in its own accounts.
The agents
Running under your accounts, each with an identity, scoped permissions, a named owner and an audit log.
The integrations
Connectors to your systems of record, in your repository, reviewed by your reviewers.
The evaluation suites
Real cases with known answers for every agent, wired into your pipeline so a regression fails the build.
The runbooks and the decision record
How to release, roll back, pause and retrain each agent, and why each design choice was made.
The context layer
How your organisation decides, written down so the next phase, and the next model, can work from it.
Your people
Owners in each department who have run the system without us in the room.
How it differs
Not one solution, and not a strategy deck.
A consultancy
A strategy engagement usually ends with a recommendation. Forward-deployed engineers write and ship the integrations, the agents and the evaluation suites in your systems, with your people, and hand over running software at the end of each phase.
Questions
Asked about enterprise AI transformation.
What is enterprise AI transformation?
Connecting an organisation's departments, systems and data through AI agents that do defined work under human oversight, phase by phase, instead of adding isolated tools. As Solonomous delivers it, it is a forward-deployed engineering programme and an active development direction, not a packaged product and not a promised result.
How is an enterprise-wide AI transformation phased?
Discovery first; then the systems and data are connected; then governed agents go in department by department, each evaluated against real cases before it touches live work. The operating model, agents on the defined work and people on the exceptions, is set up as each department goes live, and evaluation and oversight run throughout. A phase is extended only where it is technically and commercially sound.
Which existing systems can AI agents work across — CRM, ERP, HRMS, finance, procurement?
Those and others, where the organisation authorises it: customer relationship, enterprise resource planning and people systems, finance, procurement, operations and customer service. Agents reach each system through its existing interfaces and permissions, with every action logged. Which systems come first is decided in discovery, by where defined work can be measured and owned.
Do we have to replace the software we already run?
No. The programme is built around the systems you already run; agents work through their existing interfaces, identities and permissions. Replacing a system is a separate decision, made by the organisation when it is worth making, never a precondition.
Where do people stay in control as agents take on more of the defined work?
At every exception and every regulated decision. Each department keeps people with the context and the authority to decide what the agents hand over; each agent has a named owner, scoped permissions and an audit log; and your team can pause or roll back any agent. Control moves from doing each step to deciding the steps that need judgement.
How are reliability and results measured before automation is extended?
Before an agent touches live work, against real cases with known answers agreed with the people who do the work. After it does, in operation: how often work is handed to a person, how often a person overrules the agent and what each completed case costs. Automation is extended only when those measures and the owners of the work agree.
What does an AI transformation partner do that a consultancy does not?
It builds and runs what it recommends. Forward-deployed engineers work inside your systems, write the integrations, the agents and the evaluation suites themselves, and hand over running software with the runbooks to operate it. If what you need first is a strategy or a business case, we will say so on the first call.
Next step
Start with discovery,one connected function at a time.
A call with an engineer: where agents could take defined work first, what they would connect to, and how the first phase would be scoped and measured.