The problem we solve

Document extraction, customer support, invoice processing, WhatsApp bots — AI can eliminate 60–70% of manual tasks for most growing businesses. We build the integration that connects these tools to your actual workflow.

Who is this for?

  • Operations teams drowning in manual document work
  • Customer support teams handling repetitive queries
  • HR teams processing applications at volume
  • Any business with a WhatsApp customer-facing channel

What you get

  • LLM integration (Claude, GPT-4, Gemini)
  • Document / PDF extraction pipeline
  • Custom chatbot with business context
  • WhatsApp AI bot (via Business API)
  • RAG system for company knowledge base
  • Cost-optimised routing (Haiku for simple, Sonnet for complex)
  • Analytics dashboard for AI usage

Related work

Projects where we applied this service.

FinTrack Pro
Concept project
₦2.1B in transactions tracked monthly

FinTrack Pro

Personal finance and investment tracker built for young Lagos professionals. Real-time portfolio tracking, automated savings goals, and Paystack-powered instant transfers between banks.

FintechMobile
LogiSync
Concept project
1,200 vehicles tracked simultaneously in real time

LogiSync

Fleet management SaaS for mid-size Nigerian logistics companies. Real-time vehicle tracking, driver performance scoring, fuel consumption analytics, and automated dispatch scheduling.

SaaSInternal
HealthPay
Concept project
98.7% platform uptime since launch in 2025

HealthPay

End-to-end health insurance claims processing platform. Digitised claim submission, automated eligibility verification, and a provider portal for 40+ partner hospitals across Nigeria.

FintechWeb

Common questions

How much does AI cost to run monthly?

Most SME use cases cost ₦20k–₦80k/month in API fees. We implement smart caching and model routing to minimise cost without sacrificing quality.

Is our data safe when sent to an LLM?

We use API calls (not the AI company's training pipeline) and can set up data anonymisation before sending to the model. NDPR-compliant architecture by default.

How accurate is document extraction?

90–97% accuracy on most structured document types (invoices, IDs, bank statements). We build human-review fallbacks for the edge cases.

Ready to get started?

Tell us what you're building. We'll reply with a realistic scope, timeline, and Naira range within 24 hours.