We begin with your commercial objectives, then map your work products from the bottom up — across your data, workflows, dependencies and outputs — in a structured, logical and programmatic way. More often than not, the gain is in fewer steps rather than in new software, and in the overlaps between functions rather than inside any one of them.
The result is a decision-ready diagnostic and implementation roadmap, prioritised by commercial value, feasibility, data readiness, governance requirements and delivery complexity.
We begin with a paid Discovery. Tell us what you are trying to achieve commercially, and which functions are involved. We will return an initial assessment.
amir@i2ntelligence.comInstitutions accumulate processes and workflows that no longer resolve to any strategic intent. The work is to recover that intent, and to resolve the work to it.
That is what the name means. i²ntelligence — intent intelligence.
Mapping turns a process into a model that can be tested: the inputs, decision points, controls, dependencies, outputs and verification steps that determine how the work is produced.
Timesheets and operational data are usually the best available basis for this, because they connect tasks to processes and to the measures the business already reports against.
From the model we identify which work is chargeable and which is not; where bottlenecks form; where quality is constrained by the availability of experienced people; and which tools have already been bought but are not fully used.
Each finding is expressed in commercial terms, because that is the form in which it will be argued internally.
A review of one process finds what is wrong with that process. A review of the whole finds the overlaps: the same data, the same controls, the same decision points recurring across functions, where one piece of work resolves several objectives at no additional cost.
These crossovers are usually where the largest gains are, and they are invisible from inside any single process. It is the reason the assessment is holistic and hierarchical rather than a pilot.
Each step is assessed against your strategy and deliverables, to produce automation, intelligence, and streamlined integration into human workflows.
The systems that deliver automation and intelligence must remain maintainable from an accountability, cost and interpretability perspective.
You should be able to inspect outputs, audit which sources were used, understand where human review was applied, and justify the cost of serving and maintaining a model against the commercial value it creates.
Several architectures are available, and the choice is yours.
We will set out the trade-offs and implement whichever your security and governance requirements permit.
A paid, data-driven diagnostic producing the roadmap.
Building what the roadmap prioritises.
Operating and maintaining what has been built, where that is the sensible arrangement.
What we produce is yours, including the specification and the reasoning behind it. A managed service is a convenience, not a dependency.
Discovery is a paid, data-driven diagnostic across the functions in scope. It typically runs for three to six months, and closer to three where strong operational data already exists.
It requires access to timesheets and operational data across projects over time, at sufficient resolution to understand the tasks, the processes and their context.
Commercial arrangements, including risk-and-reward structures, are discussed before it begins.
Discovery is a specialist, data-driven diagnostic and advisory engagement. It does not constitute production implementation, an audit, a formal assurance engagement, regulated professional advice, or the outsourcing, delegation or transfer to i²ntelligence of any operational, regulated, fiduciary, accounting, tax, legal, employment or management function.
How much of a process will yield to specification is not known at the outset. That is why the work is conducted as research and reported as such, and why part of what is returned is the list of steps that could not be specified.
An organisation that requires a fixed scope and a guaranteed answer at signature would be better served elsewhere.
i²ntelligence is an AI research and development firm in London. Research and development is led by Amir Sani, PhD in machine learning and decision-making under uncertainty.
The method has been applied across fund services and private markets, healthcare, hospitality, and cultural institutions. A portfolio of engagements in one sector does not make a firm a specialist in it. The method is the specialism.
Client work is confidential by default. We do not name clients, publish case studies, or quote performance figures.
Tell us what you are trying to achieve commercially, and which functions are involved. We will return an initial assessment.