Service Offering

AI &
Automation

We architect intelligent systems from first principles — AI agents, LLM integrations, automation pipelines, and predictive models that make your products think, learn, and adapt.

AI isn't a feature we bolt on. It's the foundation we build from — embedded in every layer of the product so intelligence compounds over time.

40k+
AI app users served
4.8★
Avg. app store rating
<3s
AI response latency
What We Build

AI Capabilities

From conversational AI to autonomous agents — we build the full spectrum of intelligent systems that create real, measurable business value.

LLM Integration

Embed large language models into your product — Claude, GPT-4, custom fine-tunes. We handle prompting, context management, safety layers, and output structuring.

Claude API OpenAI Fine-tuning

RAG & Knowledge Systems

Retrieval-Augmented Generation pipelines that let AI reason over your private data — documents, databases, wikis — with accurate, grounded responses.

Pinecone LangChain Embeddings

AI Agents & Automation

Autonomous agents that execute multi-step workflows without human intervention — research, analysis, scheduling, communications, reporting.

Tool Use Multi-agent Pipelines

Conversational AI

AI assistants, in-app companions, and support bots that feel human — with memory, context retention, persona, and graceful escalation.

Streaming Memory Voice

Predictive Analytics

ML models trained on your historical data to forecast demand, churn, anomalies, and user behaviour — surfaced as actionable product features.

Python scikit-learn TensorFlow

AI-Powered Mobile Apps

Native iOS & Android apps with embedded intelligence — personalised content, smart recommendations, AI assistants, and offline-capable models.

React Native Expo Firebase
How We Deliver

Our AI Delivery Process

A rigorous, product-focused process built for AI — from problem definition through deployment and ongoing learning.

01

Problem Definition

Define the real business problem. AI should solve something specific, not just exist.

02

Data & Model Strategy

Select the right model, data approach, and architecture for your use case and budget.

03

Prompt Engineering

Craft, test, and red-team system prompts. Safety, accuracy, and tone dialled to spec.

04

Integration & Build

Wire AI into your product — API layers, streaming, fallback handling, and UX.

05

Testing & Safety

Edge-case testing, adversarial inputs, accuracy benchmarks, and safety review.

06

Monitor & Improve

Post-launch monitoring, user feedback loops, and ongoing model improvement cycles.

Featured Success Case

AI in Real Life

A deep look at how we designed, built, and launched an AI-native health product trusted by tens of thousands of users.

Success Case #01 HealthTech AI & Native Code

AI Pregnancy Tracker

An intelligent pregnancy companion with week-by-week AI insights, symptom tracking, and personalised guidance for expectant parents.

Week
24 of 40 active tracking
50k+
downloads
4.8★
app rating
The Problem

Pregnancy questions don't keep office hours. Expectant parents — especially first-timers — face a constant stream of concerns about symptoms, nutrition, fetal development, and emotional wellbeing that generic apps and outdated websites can't address with the nuance or immediacy they need.

Existing pregnancy apps provided static, week-by-week content that never adapted to the individual. Medical information online was contradictory and anxiety-inducing. Seeing a doctor for every small concern was impractical and expensive.

"At 3am, panicking about cramps, I got a calm, accurate, contextual answer. It felt like having a doctor friend."

— App user, Lagos, Nigeria
Our Solution

We built an AI layer powered by Claude, trained on a curated corpus of clinical pregnancy literature, that answers questions in plain language while maintaining strict medical safety boundaries. The AI knows what week the user is in, what symptoms they've recently logged, and adapts every response to their specific context.

Dynamic weekly content — nutrition, development milestones, exercise, mental health — updates automatically based on the user's stage and reported experience. Every response goes through a safety review layer that flags anything requiring professional attention.

Context-aware AI responses Clinical safety boundaries enforced 40-week adaptive content system
Delivery Process
Clinical Research Partnership
Partnered with two OB-GYN consultants to define safe AI boundaries, escalation triggers, and which questions should never be answered by AI.
Content Architecture
Structured 40 weeks × 7 content domains: nutrition, symptoms, fetal development, mental health, exercise, partner guidance, and medical checkpoints.
AI Prompting & Red-Teaming
Extensive adversarial testing — panic scenarios, edge-case symptoms, misinformation resistance. System prompt engineered for clinical accuracy without overstepping.
Mobile Build
React Native for iOS + Android. Firebase for real-time sync. Offline-first architecture for low-connectivity environments across Africa and Southeast Asia.
Community & Retention v1.2
Added peer community features. Weekly AI-written "letter to your baby" drove a 3× increase in session frequency.
Ongoing: HMO Partnerships
Piloting integration with 3 health maintenance organisations for employer maternity benefit programmes.
Technology Stack
React Native
Firebase
Claude AI
One
Signal
Sentry
"Building an AI health product taught us that the most important feature is restraint — knowing exactly when the AI should say 'please call your doctor.'"
Empatech AI team — on the AI Pregnancy Tracker build
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Build With Us

Ready to build
something intelligent?

Tell us what you want your product to think, do, and decide. We'll architect the AI system that makes it real.

Start an AI Project View All Projects
AI-native from first principles
Safety-reviewed AI systems
40k+ users served across AI products
Response within 24 hours