ROI focused AI implementation
We help enterprises orchestrate agentic operations through custom artificial intelligence solutions driven by real business Key Performance Indicators.
First we listen, then we build
Interviews at scale show how work really gets done, then become process maps, a diagnosis and a prioritised roadmap. How discovery works
Agents inside a controlled workflow
Agents absorb repetitive, document-heavy work. People approve what matters, and every step leaves an audit trail. How we build
Capability that stays in-house
Role-based tracks taught on each participant's own work, so teams can run, supervise and extend what was built. How adoption works
Organisations transformed through collaboration with our experts.
From diagnosis to daily use
One team for the whole path: diagnose how work really moves, design the architecture, build governed AI, and help people adopt it.
See how work really moves
Case-based interviews, in person and agent-led, turn a broad AI ambition into a current-state map, a ranked opportunity register and a master plan.
Current-state map
Owners, systems, controls, waiting time and rework, as the work is really done.
Opportunity register
Every candidate ranked by value, feasibility, risk and adoption effort.
Phased master plan
Sequence, dependencies and decision gates, plus what is still unknown.
Agents that show their work
We split each process into testable rules and model-driven steps. Agents extract, compare and draft; exceptions go to a named reviewer with the evidence.
Rules stay explicit
Calculations, thresholds, identifiers and access rules remain testable code.
Models where they help
Language models handle interpretation, synthesis and drafting.
Exceptions escalate
Low-confidence or high-risk outputs stop and wait for a person.
Adoption built on real work
People learn on their own cases, in tracks set by responsibility: from understanding AI, to using it safely, to building and supervising bounded workflows.
The foundations underneath
Three more capabilities run through every engagement.
AI, data & knowledge architecture
Source inventories, lineage, retrieval and permissions, so people, reports and agents work from the same definitions and evidence.
Operational software & engineering
Engineers work close to the operation until a prototype becomes something practitioners rely on every day.
Governance, security & traceability
Data classification, role-based permissions, audit trails, human approvals and exit arrangements, designed in from the first workflow.
First we listen. Then we build.
A phased loop, not a big-bang project. Each stage ends at a decision gate, so nobody commits to a build before feasibility, controls and value are understood.
- 01
Qualification
Gate: a qualified problem - 02
Discovery and master plan
Output: master plan - 03
Proof of concept, then a viable workflow
Gate: criteria met - 04
Beta, production, evolution
Gate: client approval - 05
Measurement
Output: operational metrics Then the loop starts again, with the next workflow, data source or level of autonomy.
Principles we design by
Start with the work, not the model
Build on what already exists
Security is architecture, not a disclaimer
Adoption is part of delivery
Recent work
Every figure states whether it was measured, client-reported or modelled.
Controls first. Autonomy later.
We start with bounded, assistive cases in the environment you approve. Systems read approved sources, cite their evidence and route exceptions to a person.
Your environment, your rules
We build in the tenant, cloud or private infrastructure you authorise, with read-only access to sensitive sources where possible.
No shadow IT
Teams work in approved tools under clear protocols. Client data is not used to train public models without authorisation.
Every step leaves a record
Outputs link to their source. Consequential steps log the actor, input, rule or model version, result and approval.
People decide
Agents draft, check and flag. Adverse decisions, payments and changes to core systems stay with accountable people.
Each solution is designed to the client's security policies and applicable standards, and validated per project.
The company behind the work
A private limited company based in London. Our teams work embedded with client teams, across time zones.
- Legal entity
- AI WORKIFY LTD
- Jurisdiction
- Registered in England and Wales
- Company number
- 15110606
- Incorporated
- 2023
- Based in
- London
- Working model
- Embedded with client teams, across time zones
Check the record, then talk to us
Read the cases and the controls at your own pace. When questions remain, write to us.