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Enterprise

From model to machinery.

Custom models, agentic systems, and customer engagement, engineered into the operation you run.

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ISO 27001 Certified · GDPR Aligned · Your data and IP stay yours

What this is

One house, from the data to the deployment.

Most of what is hard about production AI lives between the model and the result: the data it learns from, the evaluation that holds it to standard, the controls that govern what it does, and the deployment that keeps it running. We build all of it, the data sourced and prepared, the model trained, the system that acts on its output, and the engineering that carries the whole thing into the stack you run.

The organizations that move fastest are the ones that control the stack. When the data, the model, the agentic layer, and the deployment infrastructure are in separate hands, the build slows at every seam: version mismatches, evaluation gaps, handoff latency between vendors. We close those seams. One team engineers from the dataset to the deployed product, in your environment, on your timeline, and the IP stays with you when the engagement ends.

We have deployed these products across African markets in regulated industries spanning financial services, government, and healthcare, under data, infrastructure, and connectivity constraints few production systems are tested against. The same engineering discipline that holds under those conditions is what runs in your environment.

What we build

What we build.

Custom Model Development

The intelligence, built for your domain and owned by you. We train and adapt models on your proprietary data, and when you do not yet hold enough of it, we source and build the dataset in house. We evaluate the model against the conditions it will meet in production and deploy it into your environment with the weights in your hands. What ships is a model that carries knowledge a general one has never seen, and a pipeline you can run, retrain, and extend as your data grows.

Includes: data sourcing and preparation, training and adaptation on your proprietary data, evaluation against production conditions, deployment in your environment, and the weights and pipeline delivered to you.

Agentic AI

The system that acts, governed at every step. Where a model answers, an agent does: it carries multi-step work across your tools and data, proposing actions, staging the consequential ones for human approval, and executing the rest within permissions you set. Orchestration sequences the work, evaluation scores it against defined cases before it ships, test scenarios drawn from your real workflows including adversarial inputs and out-of-scope requests, and every action runs with a full, attributable trail. Autonomy with a record, and a checkpoint wherever it matters.

Includes: orchestration across your systems, an evaluation suite run before deployment, staged human approval on consequential actions, and a complete, attributable trail of every action.

Customer Engagement

AI that meets your customers on the channels they already use, voice, WhatsApp, SMS, and USSD. Grounded in your product, policy, and operational documentation, it answers accurately within the scope it has been trained and evaluated on, and routes to a human agent when the complexity or stakes of a case warrant it. Every conversation is logged and the system is instrumented so edge cases surface as data rather than complaints, and improvement cycles are closed on evidence rather than intuition.

Includes: grounded conversation across voice, WhatsApp, SMS, and USSD, evaluation against your real interaction cases before deployment, human handoff routing with configurable triggers, and a complete, auditable conversation log.

From proven to running

From proven to running.

We confirm the product is the right one, through an AI Opportunity Assessment, or directly when you already know what you need.

We build and integrate it into your systems and data, a forward deployed team working inside your environment.

We deploy it into production, operate it against the numbers that matter, and pass your team the controls as they take it on.

Ready for security review and procurement. Documentation available under NDA. Learn how we work.

Engineered to run

Built to the standard production demands.

A product is judged after launch, not in the demo, and we engineer for that from the first line.

Built into your stack

Deployed into the systems and data you run through your own interfaces, so the product operates inside your operation rather than alongside it. Standard APIs into your existing infrastructure. No rearchitecting required on your side to make the integration work.

Model-agnostic by design

Built to run on the strongest models available and to switch as the field moves, so the product outlasts any one of them. Provider lock-in is an architectural choice. We do not make it.

Observable in production

Instrumented so you can see what the system did and why, with the record and the controls to act on it. Performance, failure modes, and model drift are visible in the observability layer we build into the product, so operation generates the data that drives the next improvement cycle rather than accumulating silently.

Proven in hard conditions

Engineered and deployed under low-latency requirements on variable connectivity, African language processing at production scale, and identity verification across national ID types that general systems are calibrated for in theory and tested against in practice. The same engineering that holds under those constraints runs in your environment.

Security and IP

Your data and your IP stay yours.

We build in environments you approve, to a security standard your reviewers can verify, and the product belongs to you.

Your data, isolated

We work in your environment or an isolated one you approve, and your data trains nothing for anyone else.

The IP is yours

The model, the pipeline, and the code are yours to hold and to run.

Secure by certification

ISO 27001 certified information security and GDPR aligned handling, documented for security and procurement review under NDA.

Yours to operate

We build your team into running the product, so the controls end in your hands.

Who we build for

Who we build for.

We build for the operators putting AI into the workflows their business depends on, in the industries where performance is measured, regulated, and consequential.

Financial services

Banks, lenders, fintechs, and microfinance institutions operating under regulation, where fraud patterns shift faster than manual rules can track, credit decisions carry portfolio-level risk, and the customer base includes millions of people whose primary financial interface is a mobile phone. The constraint in financial services AI is not the model. It is data quality at the transaction level, model performance inside a risk and compliance framework your regulators can examine, and the channel infrastructure to reach customers at scale without a branch network.

Where we fit: Custom Model Development for credit scoring and fraud detection, Agentic AI for compliance and reconciliation workflows, Customer Engagement across USSD, mobile money, and voice.

Government and public sector

Revenue authorities, land registries, immigration services, and social program administrators running document-heavy workflows at volume, where processing speed and accuracy directly determine service delivery quality and revenue capture. Government data is structured, vast, and largely unprocessed at speed. The decision workflows that govern permit issuance, tax assessment, and benefit eligibility carry the same structure as the systems that automate them, and the compliance requirements are higher than in most private sector equivalents.

Where we fit: Agentic AI for document processing and approval workflows, Customer Engagement via USSD and voice for citizen-facing services, Custom Model Development for document classification and entity extraction.

Agriculture and agribusiness

Commodity traders, cooperative networks, input suppliers, agricultural lenders, and extension service operators whose operational decisions, what to buy, where to route it, which farmers to finance, depend on data that is rarely connected to the systems that act on it. Satellite imagery, soil data, weather feeds, and transaction records sit in separate systems. The farmers who are the end of the chain use feature phones. The advisory and procurement infrastructure that should serve them does not reach them at the channel level.

Where we fit: Custom Model Development on crop, weather, and supply chain data, Customer Engagement via voice and SMS for farmer-facing advisory, Agentic AI for procurement and logistics coordination.

Energy and utilities

Power distributors, oil and gas operators, and renewable energy developers running asset-intensive operations where predictive maintenance is the difference between a scheduled intervention and an unplanned outage, and where compliance reporting requires assembling data from sensor logs, inspection records, and maintenance histories that most teams cannot process at the speed regulation demands. The data to predict failure already exists. The system to act on it before the failure occurs is the gap we close.

Where we fit: Custom Model Development for predictive maintenance and anomaly detection, Agentic AI for inspection and maintenance approval workflows, Customer Engagement for outage communication and utility services.

Healthcare and life sciences

Hospital networks, health insurers, pharmaceutical operators, and public health program administrators where clinical documentation is the highest-cost manual workflow, claims adjudication generates the largest volume of structured errors, and patient engagement at scale requires a channel that reaches patients where they are. Clinical text is dense, domain-specific, and consequential. The systems that process it must carry the accuracy standard the clinician signing off requires, and the governance to keep the human in the loop on every decision that warrants it.

Where we fit: Custom Model Development for clinical NLP and claims processing, Agentic AI for prior authorization and document workflows, Customer Engagement via WhatsApp and voice for patient intake and follow-up.

Frequently Asked Questions

Questions buyers ask before they build.

Do we own the model you build for us?+

Yes. The model, the weights, the pipeline, and the code are yours. We build in your environment or one you approve, deliver the weights into your hands, and leave you a pipeline you can run, retrain, and extend as your data grows.

Which models do you build on?+

The strongest available for the task. We are model-agnostic by design, building so you can run on the best model for the job and switch as the field moves, rather than tying a product to a single provider that ages with it.

How do you know it will hold in production?+

Evaluation before deployment. Every product is scored against a defined suite of cases drawn from your real data, load, and edge conditions, so its behaviour is measured against production before it reaches a user, not after.

What keeps an agent from doing something it should not?+

Permissions you set and authority you keep. An agent proposes actions, stages the consequential ones for human approval, and executes the rest within limits you define, with a full, attributable trail of every action it takes.

What happens to our data?+

It stays yours. We work in your environment or an isolated one you approve, your data trains nothing for anyone else, and handling is documented for security and procurement review under our ISO 27001 certified information security management system.

What does retraining look like after deployment?+

We build the retraining path into the product from the start. The instrumentation that monitors the deployed system surfaces the cases where performance is degrading or edge cases are accumulating. We scope the retraining cycle during the engagement so your team understands the triggers, the process, and who holds the decision to retrain, before the first version ships.

Closing CTA

Put a product into production.

Start with an assessment that proves the highest-value build, or arrange a briefing if you already know the product you need.

Request an AI Opportunity Assessment Arrange a briefing