AI Workflow Automation
We find the repetitive work eating your team's week — reconciliation, data entry, approvals, reporting — and hand it to software that never gets tired.
AI Consultants · Nairobi, Kenya
We find the repetitive work quietly draining your week — reconciliation, data entry, quotations, the same WhatsApp question fifty times a day — and we build systems that do it for you. Practical AI, in production, in weeks.
Or call +254 711 362 029 — free 30-minute scoping call, no obligation.
We connect AI to the systems Kenyan businesses already run on
Plus whatever else you use — if it has an API, a database or an inbox, we can work with it.
The short version
What is an AI consultant in Kenya?
An AI consultant in Kenya is a specialist who helps a business work out where artificial intelligence will genuinely save money or win revenue, and then builds and deploys those systems into the tools the business already uses. The work usually covers four things: an audit of current workflows, a costed roadmap, building the first automations or AI agents, and training staff to run them safely under the Kenya Data Protection Act, 2019.
That is the textbook answer. Here is the honest one: most companies do not have an AI problem. They have a process problem that AI happens to be very good at fixing. Our first job is telling you which of the two you have — and if the answer is “you do not need AI for this, you need a better spreadsheet”, we will say so.
Is this you?
If you nodded at two or more, there is a project here worth doing. It usually pays for itself before the quarter ends.
For everyone in the room
Boards, operations managers and engineers all need to understand this — but not in the same words. Switch between the two versions below. Nothing is dumbed down; only the vocabulary changes.
The same answer, two ways
What problem are we actually solving?
Your business runs on people doing work that a machine could do.
Every week, your team spends hours copying numbers between systems, chasing approvals, retyping M-Pesa statements into Excel, answering the same customer question over and over, and hunting through folders for one document. None of that work makes you money. All of it makes people tired, and tired people make mistakes that cost money.
We come in, watch how the work really flows (not how the manual says it flows), and pick the one or two things that are costing you the most. Then we build a system that does those things for you — quietly, in the background, day and night, without lunch breaks or resignations.
Your staff keep the tools they already know. WhatsApp is still WhatsApp. Excel is still Excel. The difference is that the boring parts fill themselves in, the customer gets an answer in ten seconds instead of two hours, and your Monday report is waiting for you on Monday morning rather than Thursday.
The plain-English promise
Fewer hours on work nobody enjoys. Faster answers for customers. Numbers you can trust. And a human still in charge of anything that involves money or a difficult conversation.
We deploy deterministic automation and LLM-based agents against instrumented process bottlenecks, with humans in the loop wherever the blast radius is financial.
Engagements start with process mapping and baseline instrumentation: cycle time, touch count, error and rework rate, and cost per transaction. That baseline is what we are held to later, and it is what stops “AI project” from meaning “expensive demo”.
A typical build looks like an orchestration layer (n8n, Temporal, Airflow or Make, depending on scale and who has to maintain it) sitting over your systems of record — Safaricom Daraja for M-Pesa C2B/B2C and STK push, WhatsApp Business Cloud API for messaging, your ERP or accounting package (Odoo, Sage, QuickBooks, Xero), and object or document storage. Where language understanding is needed we use retrieval-augmented generation over your own corpus, chunked and embedded into pgvector or a managed vector store, with hybrid keyword plus semantic retrieval and re-ranking, because pure vector search fails badly on Kenyan proper nouns, product codes and account numbers.
Agent behaviour is constrained by narrow, typed tool definitions rather than open-ended prompts: the model chooses among a handful of permissioned functions, each with server-side validation, rate limits and idempotency keys. Anything that moves money, issues credit, or sends a legally binding commitment lands in a human review queue. Everything is logged as an immutable audit trail with the prompt, retrieved context, tool calls and outcome, so behaviour can be explained after the fact — which is both an operational necessity and a Data Protection Act one.
Before go-live we build an evaluation harness from your real historical cases: an offline set with expected outputs, accuracy and hallucination rate thresholds, and regression runs on every prompt or model change. Post-launch we monitor drift, escalation rate, containment rate and cost per resolved interaction. Models get swapped; the evaluation set is the asset that survives.
The engineering promise
Version-controlled, documented, observable, and reversible. You get the repository, the runbook and the evaluation set. No lock-in to a consultant who is the only person who understands the system.
Reference architecture we work from: channels on the left, orchestration and guardrails in the middle, your existing systems of record on the right. Every project is a subset of this.
A concrete example
Month-end reconciliation at a mid-sized Kenyan distributor — a process we see in almost identical form at hundreds of companies.
Before — 3 people, 2 days
After — 1 person, 20 minutes
An honest note about the numbers
The example above is an illustration of a pattern, not a claim about a specific client. We do not publish invented statistics. In your first call we build the “before” column from your process, with your real volumes and salaries, so the business case is yours and not a brochure’s.
What we do
Most clients start with one and grow into the others. You do not have to buy the whole programme to get value from the first project.
We find the repetitive work eating your team's week — reconciliation, data entry, approvals, reporting — and hand it to software that never gets tired.
A WhatsApp and website assistant that answers customers in English and Kiswahili, qualifies leads, checks order status and escalates to a human when it should.
An honest map of where AI will make you money, where it will waste your money, and what to do first — costed, sequenced and tied to your numbers.
When off-the-shelf will not fit: document intelligence over your own files, forecasting on your own history, and integrations into the systems you already run.
Practical, hands-on sessions for executives, managers and frontline staff — using your real documents and your real tasks, not generic examples.
Most failed AI projects are really failed data projects. We clean, connect and govern your data so the clever part has something solid to stand on.
Built for here, not imported
Playbooks written for London or San Francisco assume card payments, clean master data, reliable power, and customers who use email. Kenya runs differently — and that changes the design, not just the marketing.
Most of your cash story lives in mobile money, not a bank feed. We build directly against the Safaricom Daraja API — C2B, B2C, STK push, callbacks and reconciliation — and handle the messy realities: partial payments, wrong reference numbers, one till for three branches.
Your customers will not fill in a web form and they will not email. They will WhatsApp you at 21:40 and expect an answer. We build on the official WhatsApp Business Cloud API, so you get automation without risking the ban that comes with unofficial tools.
KRA eTIMS invoicing, SASRA reporting for SACCOs, IRA returns for insurers, and the Data Protection Act, 2019 with its ODPC registration duties. Automation that ignores these creates a bigger problem than it solves.
We design for intermittent connectivity and modest devices: queued and retried jobs, offline-tolerant capture, light pages, and SMS or WhatsApp fallbacks when a browser is not realistic. A system that only works on fibre is not a system.
Working across Kenya
Based in Nairobi. Delivering to Mombasa, Kisumu, Nakuru, Eldoret, Thika, Naivasha and beyond — and to clients elsewhere in East Africa.
How we commit
We do not publish borrowed case-study statistics. These are commitments about how we work — the things entirely within our control, which you can hold us to from the first call.
See it working
Not a menu tree. Not “press 1 for sales”. A WhatsApp agent that understands the question, checks the real system, gives a real answer, and hands over to a person the moment it should.
How we work
You always know what happens next, what it costs, and what you get at the end of each stage. You can stop after any of them and still own something useful.
The tasks that automate most cleanly, in our experience. Higher means less human judgement is needed — and therefore a faster, cheaper first project.
Thirty minutes on a video call or WhatsApp. You describe the pain; we ask uncomfortable questions about volumes, exceptions and who actually does the work today. You leave with an opinion, whether or not you hire us.
One to two weeks. We shadow the real workflow, measure the baseline, and score candidate automations by value, effort and risk. You get a costed, sequenced roadmap you own outright.
Two to six weeks. We build the highest-value automation end to end, integrated with your live systems, with a human review step wherever money moves. Fixed price, agreed up front.
We move it into daily operations, train the people who will use it, and write the runbook in plain language. Your team must be able to run this without us.
Either we hand over completely, or we stay on a monthly retainer to monitor, tune and build the next automation. Your choice, reviewed every quarter, no lock-in.
Who we work with
The technology is similar; the constraints are not. A SACCO’s reporting obligations, a clinic’s patient confidentiality and a logistics firm’s driver network each change the design.
Member onboarding, loan appraisal support, SASRA-ready reporting.
Document verification, fraud triage, customer service agents.
Claims intake, policy document Q&A, renewals follow-up.
WhatsApp ordering, stock queries, M-Pesa reconciliation.
Dispatch, proof-of-delivery capture, customer ETA updates.
Appointment handling, records summarisation, claims paperwork.
Farmer support lines, yield and price analytics, field data capture.
Contract review support, proposal drafting, research and briefs.
Quality checks, maintenance prediction, procurement paperwork.
Booking enquiries, multilingual guest support, review response.
Admissions enquiries, marking assistance, timetable and fee queries.
Donor reporting, M&E data cleanup, field survey processing.
Why us
Plenty of firms will sell you a strategy. We write the code, connect the APIs and stay until it runs in production. The roadmap is a means to a working system, not the deliverable.
If a KES 4,000 tool or a fixed spreadsheet solves your problem, we will tell you and send you on your way. A short honest engagement beats a long disappointing one.
You get a number before we start, not a running meter. If we misjudged the scope, that is our risk to carry, not yours.
Code, prompts, evaluation sets, documentation and accounts are yours. No proprietary black box that only we can maintain, no hostage situation at renewal.
Anything touching money, contracts or a complaint routes to a person for approval. Automation should remove typing, not remove judgement.
We build for M-Pesa, WhatsApp, patchy bandwidth and Kenyan compliance — using the same engineering discipline you would get from a serious international firm.
Insights
Straight answers to the questions we get asked most — costs, tools, compliance and what actually works here.
What AI consultants in Kenya actually do, what a fair price looks like in KES, the questions that expose a weak firm, and how to structure the contract so you keep what you paid for.
Real KES ranges for audits, chatbots, document automation and custom builds — plus the running costs nobody quotes you for, and how to work out whether a project pays for itself.
Why WhatsApp is the only channel that matters for most Kenyan customers, how the official Business API works, what it costs per conversation, and how to build an agent people do not hate.
Questions
The eight questions we are asked in almost every first conversation.
An AI consultant in Kenya helps an organisation identify where artificial intelligence and automation will genuinely save money or win revenue, then designs, builds and deploys those systems into the tools the business already uses. In practice that means auditing your current workflows, choosing the small number of processes worth automating first, building them — chatbots, document processing, reconciliation, forecasting, reporting — integrating them with local systems such as M-Pesa, WhatsApp Business and your accounting package, and training your staff to run them safely.
Most Kenyan engagements fall into three bands. An AI opportunity audit typically starts around KES 75,000 and gives you a costed roadmap. A first working automation or AI agent typically starts around KES 250,000 depending on how many systems it must talk to. An ongoing partner retainer typically starts around KES 150,000 per month. We publish indicative ranges on our pricing page and give you a fixed quote before any work starts.
No. The smallest businesses often get the fastest return, because one person is doing five jobs and every hour returned is immediately visible. If you have a WhatsApp line that never stops buzzing, an M-Pesa statement you retype into Excel, or a quotation process that takes a day, there is something here for you. What matters is not headcount — it is whether a repetitive, rule-heavy task is eating real hours every week.
In almost every project we run, the answer is no — the work simply moves. Automation takes the copying, typing, checking and chasing; your people move to the judgement, the relationships and the exceptions. We design deliberately for this: anything touching money, contracts or a customer complaint routes to a human for approval. The honest framing is that AI replaces tasks, not people, and businesses that adopt it early tend to grow into the freed-up capacity rather than shrink.
Yes, when it is done properly. The Kenya Data Protection Act, 2019 governs how you collect, process and store personal data, and it applies to AI systems exactly as it applies to any other system. We design around it from day one: data minimisation, a lawful basis for processing, clear retention rules, access controls, audit logs, and choices about where data is processed. If you are a data controller or processor that must register with the Office of the Data Protection Commissioner (ODPC), we will tell you and help you document the system properly.
Two to six weeks for a first automation in production is typical, and an AI opportunity audit takes about two weeks. We deliberately scope the first project small enough to ship fast, because a working thing your team can touch beats a strategy document nobody reads.
No. We are based in Nairobi and meet clients there in person, but the work itself is delivered remotely across Kenya — Mombasa, Kisumu, Nakuru, Eldoret, Thika and beyond — and elsewhere in East Africa. Most projects run on video calls, WhatsApp and shared screens, with on-site visits where they earn their keep, such as process discovery and staff training.
That describes most businesses we meet, and it is not a blocker. Part of the job is deciding what actually needs cleaning versus what can be worked around. Modern document AI reads scanned invoices, delivery notes and handwritten forms well enough to be useful, and we frequently start there — turning paper into structured data is often the automation with the highest return.
Still wondering about something?
Start here
Book a free 30-minute call. We will map one process end to end, tell you honestly whether AI is the right answer, and put a number on what fixing it is worth. No slide deck, no jargon.
Nairobi-based · We reply the same working day · English & Kiswahili
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