Directed intelligence
In build · 2026
For the institutions that run economies
Directed intelligence for institutional decisions.
The institution’s data, decisions and memory
Used for decisions such as
- Which of forty candidate projects is funded this cycle.
- Where an intervention stalled, and why.
- How a ten-year capital budget should be sequenced.
- Who receives credit, and on what terms, in markets where conventional credit data is thin.
Routed and swapped · nothing of the institution’s is held here
OLU is data and AI infrastructure for finance and planning ministries, development finance institutions, sovereign funds and large enterprises. It connects to the systems and registers an institution already keeps, joins them into one record, and applies AI analysis to the decisions that record informs. Staff ask questions in plain language and get answers that cite their sources; decision models show the options, what each costs and how confident each figure is; and every decision is kept with the reasoning behind it. It runs inside the institution’s own environment, so the data stays in its custody.
- Frontier models Routed across the best available, swapped as the field moves
- Cloud and compute Sited where the institution’s regulation requires
- Enterprise systems Read in place, inside the institution’s perimeter
What it does
What OLU
does
An institution’s information usually sits in separate systems, kept by separate departments in different formats. OLU brings it together and applies it to the decisions the institution has to make, without moving it out of the institution’s environment.
- 01
Connects
Reads the systems, registers and documents the institution already keeps, where they sit: accounting and enterprise systems, statistical and administrative registers, management accounts, board packs and contracts. It does not replace them.
- 02
Joins
Combines records held by different departments into one, so a question that crosses them is answered from all the evidence rather than from one register at a time.
- 03
Answers
Staff ask questions in plain language and receive answers that cite the source records and documents.
- 04
Models
Decision modules set out the options on a specific decision, what each costs, and the confidence of every figure. Modelled values are kept separate from observed ones, and assumptions are versioned and open to the institution’s revision.
- 05
Drafts
Prepares committee papers, reports and briefing notes from the record. Nothing is released without review by the institution’s own staff.
- 06
Keeps the record
Stores each decision with the reasoning and evidence behind it, searchable and attributable, so it can be defended later and is not lost when staff move on.
Each decision module is built for a named decision and the questions that go with it, and says so when a question falls outside them. The worked example below shows one.
Worked example
Execution across
nine national
programmes
A West African ministry of planning carries the human capital pillar of a five-year national development plan: nine programmes across education, health, vocational training and school feeding. The planning directorate arbitrates between them and a monitoring committee reviews them, and the two had been working from separate assemblies of the same material.
OLU ran a paid Directed Works day against one question: where is execution falling behind, and what does moving money between programmes do to the outcome? The module was delivered in French and English, on published data only. It works with three operational levers rather than budget lines (coverage, execution and timing), each with its fiscal cost and its confidence level.
Schematic · not a screenshot · no client data · structure only
Coverage
How many are reached, across nine programmes
Rises with reach
Execution
The share of an allocation actually spent in cycle
Broadly neutral
Timing
Where in the five years a programme is sequenced
Shifts between cycles
Every value carries its confidence, and the modelled-versus-observed distinction stays in front of the reader. Coefficients are versioned, annexed and open to the directorate’s revision. The module claims no causation.
The levers · operational decisions, not budget lines
How many are reached, across the programmes in scope
The share of an allocation actually spent in cycle
Where in the five years a programme is sequenced
Turn this on to read the module against itself. The uncertainty band widens to ±60%, the transmission coefficients lose their defaults, and every figure is marked for what it is.
Modelled human capital index, 2030
Components · the index is their product
The questions this module is directed at
Execution stands at 29 per cent of full. Closing that gap alone carries the 2030 index from 0.298 to 0.478, a gain of 0.180.
Almost all of the movement falls on education, because that is where the execution lever transmits. The gap itself is read from published execution rates; the 2030 figure is modelled.
The set is fixed when the module is built. A module answers the questions it was directed at and says so when a question falls outside them, which is what makes an answer defensible after the fact.
The index is a product, not a sum. Excellent schooling on failing health does not produce average human capital — it is capped by the weaker component, which is why the next unit of effort is worth most where the index is thinnest. Coefficients are versioned, annexed and open to the directorate’s revision. The module claims no causation.
A consignment of medical supplies is being scheduled for District K’s seventeen clinics. Stores are allocated the way stores are allocated everywhere: the next truck goes where stock is lowest. Below is the ledger, the allocation any competent officer would draw from it — and what the same ledger says when read with two other registers.
Stores ledger
Stock on shelf, District K
- Six clinics
- 34 days of stock
- Eleven clinics
- 7 days of stock
- Allocation drawn
- eleven first · six last
“The six are covered for a month. The consignment goes to the eleven. Correct, on this ledger — and it is how every truck in the country is routed.”
Attendance register
Clinic attendance, District K
- District, year on year
- −9%
- Read as
- seasonal
- Action
- quarterly review
“A soft year across the district. Flagged for the quarterly review.”
Works register
Route N-7, river crossing
- Rehabilitation status
- suspended
- Suspended since
- Aug 2027
- Priority class
- routine
“A delayed rural crossing among forty. Carried forward to next cycle.”
Every reading above is competent. The allocation is the one any storekeeper would draw, and it is about to be actioned. Read the three registers together before the trucks are loaded.
Rules the module runs under
No causal claim
The module models trajectories under declared assumptions. Coefficients are versioned, annexed and open to the directorate’s revision.
Two lenses, one platform
The committee view carries synthesis. The working layer — tables, assumptions, memory — stays with the team that has to defend it.
Built to be tested
A critical-reading mode strips the coefficients of their defaults, widens the uncertainty band, and keeps the modelled-versus-observed distinction in front of the reader throughout.
Three-part data regime
State data stays the state’s, in jurisdiction. Outputs and deliberative memory are the ministry’s. Method improvements carry neither and benefit every deployment.
Who it’s for
The institutions
OLU is built for
It is directed at the decisions those institutions find hardest — the ones that are large, consequential and expensive to reverse.
Government and public administration
Ministries of finance, planning, economic development, health and digital affairs. Premier’s and governor’s offices. Statistics agencies, revenue authorities, border and customs administrations, roads agencies.
Development and sovereign finance
Development finance institutions, sovereign wealth funds, national infrastructure funds, pension administrators and multilateral development banks operating on the continent.
Credit and financial services
Banks and non-bank lenders operating where conventional credit data is incomplete, together with credit guarantee schemes and public lending programmes.
Large enterprise
Groups operating across several African jurisdictions — infrastructure, construction, resources, logistics, agriculture, security — where the same decision must be made consistently under very different regulation.
Where it fits
- An institution has been given a mandate it does not yet have the tools to execute.
- It is under pressure to demonstrate how a decision was reached, rather than merely what was decided.
- It holds substantial data that regulation or policy prevents from moving offshore.
Where OLU declines the engagement
Where what is wanted is a generic tool, unconfigured to the institution and its decisions. Where the decision in question sits with a technology function rather than with the person accountable for the outcome.
In both cases, no one in the institution would own the result.
Eight verticals
Verticals
and their stage
OLU works through direct engagement with institutions rather than a broad commercial launch. Three verticals are in active engagement. The other five open when an institution in them asks.
- GovernmentOLU Ministries, premier’s and governor’s offices, national agencies In engagement
- FinanceOLU Banks, non-bank lenders, credit guarantee schemes and public lending programmes Sequenced
- InvestmentOLU Sovereign funds, development finance institutions, asset managers, insurers and family offices In engagement
- SecurityOLU Duty of care, executive protection, major-event security. Contains AKILI In engagement
- InfrastructureOLU Capital programmes, roads, ports and utilities agencies Sequenced
- ConstructionOLU Delivery and contractor performance across jurisdictions Sequenced
- HealthOLU Ministries of health and national health programmes Sequenced
- FarmOLU Agricultural production, input finance and land systems Sequenced
GovernmentOLU
In engagement at ministerial level in West, Central and Southern Africa, and at premier’s-office level in a South African province, where it has been applied as a single instrument across health, education and economic development inside one administration.
InvestmentOLU
In engagement with major infrastructure funds and with sovereign and development finance institutions, on portfolio management, capital allocation and project selection.
GlobalWatch, within AKILI
The traveller risk and duty-of-care module, built to the ISO 31030 framework, moving into deployment with blue-chip global enterprises.
Several of these engagements have progressed through paid engagement into production scoping. Counterparties are described by type here. A number are subject to confidentiality undertakings, and specific names can be given in conversation where it is useful to do so.
How it’s built
The Directive
OLU is installed in the institution’s own environment, or in in-country infrastructure of its choosing. It uses AI models from several providers and can switch between them as the field changes, so the institution is not tied to one supplier. A model receives the question and the parameters the institution has approved, never the source records, and every request is logged. There is no path for exporting the institution’s data, because none was built.
The principle is cognitive data sovereignty: the institution owns its data and the analysis, models and decision history built on it.
Institutions served
Data and decisions stay above the line
- Government and public administration
- Development and sovereign finance
- Credit and financial services
- Large enterprise
- Context Intelligence
- Institutional Memory
- Multi-Jurisdiction Routing
- Sovereignty by Architecture
Built and owned by OLU
- Frontier models
- Cloud and compute
- Enterprise systems
Input layer · routed, and swapped as the field moves
OLU builds no AI model of its own and sells no cloud or compute. That leaves it free to use whichever providers suit the institution, and to change them.
Above the line · the institution’s data, decisions and memory
The boundary
Set by the institution’s regulation, not by contract
Crosses down
- The question, expressed as a task
- Method, coefficients and assumptions
- Non-identifying parameters
A question is not a record. What descends is what the institution has approved for the purpose, and it is logged.
Crosses up
- The result, and its confidence
- The reasoning that produced it
- Method improvements, carrying no content
Everything returned is attributable and versioned, so the decision can be defended after the fact.
Never crosses
- Source records and registers
- Institutional identifiers
- Deliberative memory
No export path exists for these, because none was built. Counterparties test this property hardest.
Below the line · routed, and held by no one
The distinction that carries the claim is between a question and a record. The first descends under the institution’s own authorisation and is logged; the second does not descend at all.
Context Intelligence
The situation, the jurisdiction, the history
The platform carries the specific situation, jurisdiction and history behind a decision, rather than treating each request as though it had arrived from nowhere.
Institutional Memory
Prior decisions and the reasoning behind them
Decisions are kept together with the reasoning that produced them. The record becomes more useful the longer it is kept, and it belongs to the institution.
Multi-Jurisdiction Routing
Several legal regimes at once, as the default
It operates under several legal and regulatory regimes at once, which is the normal condition for cross-border work on the continent.
Sovereignty by Architecture
The data stays in the institution’s custody
There is no export path for the institution’s data, because none was built. Unlike a contractual commitment, this cannot be changed after signature.
Position
Independent of
the outcome
The decisions OLU is used for have parties on either side: which projects are funded, which supplier wins the work, which programme goes first. OLU has no stake in those answers. It does not sell the technology an institution runs on, it owns none of the projects being weighed, and it does not compete with the institutions it works for.
Blessing Rugara has held that role for some twenty-five years in African corporate finance, as an independent financial intermediary to large institutions. OLU applies it to decisions made with AI.
Most AI products require an institution to move its data onto the vendor’s platform. The data then sits under another country’s law, and the vendor’s products learn from it. Data sovereignty requirements are appearing in procurement documents across the continent for that reason. OLU is built so the data does not need to leave.
How an engagement begins
From introduction
to rollout
The first conversation is a listening one: nothing is presented, no proposal is made, and no commitment is sought on either side. Where both parties find it worth continuing, the next stage is Directed Works — one named problem, working software within two weeks, paid and narrowly scoped by design.
- 01
Introduction
A name and a short note
Somebody who knows both parties puts the name forward. No commitment is sought at introduction, and none is offered.
- 02
Conversation
One meeting to hear the problem
The first conversation is a listening one. OLU hears the decision the institution is carrying. Nothing is presented and no proposal is made.
- 03
Directed Works
One named problem, working software within two weeks
A paid engagement, narrowly scoped by design. It is how OLU demonstrates capability rather than describing it. An institution that goes no further still owns what was built for it.
- 04
Lighthouse Partnership
The platform against a defined operational scope
A named programme, a function or a region. Operational fluency is established and the capability is retained inside the institution’s own perimeter.
- 05
Institutional Rollout
Full operating geography and scope
The platform extends across the institution’s full operating geography. By this stage every claim has been tested on work the institution commissioned itself.
Open today Reached on evidence from the stage before
What is asked of the institution
- Nothing
- An hour
- A defined scope
- A defined programme
- A mandate
An institution may stop at any gate, and keeps what has been built to that point.
The people
Team and
advisory board
Blessing Rugara
Chief Conductor
Executive Chairman of Circle Capital Global Holdings, which has advised on more than €3 billion of completed transactions, and a member of the consortium that acquired ten per cent of Capitec Bank in its early years. He holds a Juris Doctor from the University of Minnesota Law School and was a partner at Mackall, Crounse & Moore in Minneapolis. In Zimbabwe he has chaired the Finance Committee of the ZBC board and the ZIFA restructuring committee.
Some twenty-five years as an independent financial intermediary to large African institutions, the party both sides could rely on. OLU applies that role to a different kind of decision.
Dr Charlie Maere
Chief Technology Officer
Doctorate in computer science, specialising in artificial intelligence and distributed systems. Has led national-scale health information deployments across more than 750 hospitals in Malawi under a PEPFAR/CDC programme, and technology delivery across sixteen countries as a global director of digital health and data analytics. Formerly chief technology officer of an engineering firm running teams across the United States, China, South Africa and Ukraine. Published in machine learning, computer vision and medical imaging. Leads the design and engineering of The Directive.
Tinashe Jaramba
Head of Platform Strategy
An aerospace engineer by training. He leads product direction, implementation planning and client success, mapping platform capability against each institution’s requirement.
Harold Rugara
Head of Institutional Solutions
An electrical engineer and a senior business leader. He leads the design of institutional workflows and the implementation of the platform with client teams.
Advisory board
Ibrahima Guimba-Saidou
Chief Executive of the Partnership for Digital Access in Africa, after a career in senior international technology and telecommunications leadership across the continent.
Matsi Modise
Founder of Furaha Afrika Holdings, with governance roles across fintech, venture capital and financial services.
Dr Appolinaire Tiam
Physician and public health leader, advising on HealthOLU and leading ministry-level health engagement across Southern and Central Africa.
Temi Adeniji
Principal at Porci Capital LLC, bringing international media, rights and investment experience across African and United States markets.
Epiphany Vera
Holds intellectual property in sound, from a former company that produced the audio for Sony and Microsoft gaming platforms. Boston-based.
AKILI is built alongside operators whose practice spans more than three decades of executive protection and major-event security across multiple jurisdictions.
Contact
Arrange a
first conversation
Blessing Rugara takes these conversations directly, and the first one takes about an hour. Where a suggested institution sits close to work already under way, we say so at once rather than let two approaches arrive from different directions, and we revert on the outcome of any introduction as a matter of course.
- Offices
- Mauritius · Dubai · Johannesburg