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AI Application Development & IntegrationFrom intent to action.

AI applications & integrations

We design AI applications and integrate models into the software you already run — so they can read your data, use your tools and get real work done, safely.

What’s included

01

AI applications

New products and features where AI does the work, not just the talking.

  • Voice and chat agents that answer, book, update records and escalate to a person
  • Document intelligence: extract, classify and summarise long documents, with every claim traced to its source page
  • Internal assistants that search and answer over your own knowledge, respecting access controls
02

AI integrations

Bring language models into the product you already have — no rewrite, no lock-in to a single model vendor.

  • LLM features added to existing web and mobile apps
  • Tool use and workflow automation over MCP, APIs and webhooks, with permissioned actions
  • Retrieval-augmented generation (RAG) that keeps answers grounded in your current data
  • Model selection, prompt design and cost control across providers
03

Guardrails are part of the architecture

AI that touches customers, money or records has to be accountable. We build that in from day one.

  • Policy before prompts: every action an agent can take passes an explicit policy layer
  • An audit trail of tool calls, decisions and outputs
  • Human review for anything published, paid for or irreversible
  • Test conversations and evaluation sets that run before every change

Related work

Where we’ve done this before

AIVoiceIntegrations

Tekera

Voice agents that turn intent into action.

An AI voice agent platform where each use case ships as a pack — prompt, policy, adapter and test conversations. A tool gateway executes actions over MCP and webhooks, enforces policy on every call, and keeps an audit log.

ElevenLabs · MCP · Webhooks · Agents as code

AICivic techData

Ukaguzi

A 60-second understanding of Kenya’s audit reports.

A mobile-first civic data tool that turns dense Auditor General reports into plain-language summaries. Reports move through a pipeline — detected, extracted, AI-processed, human-reviewed, published — and every finding links back to a verbatim quote and page in the source PDF.

Document AI · Review workflow · Mobile web

Frequently asked questions

Can you add AI to an app we already have?

Yes. Most of our AI work is integration: connecting a model to your existing database, APIs and user roles so it works inside the product your customers already use.

Which AI models do you work with?

We are model-agnostic and choose per use case — commercial LLM APIs, open-weight models, and speech platforms for voice agents — balancing quality, latency, cost and where your data is allowed to go.

How do you stop an AI agent from doing something it shouldn’t?

Agents only act through tools we define, each behind a policy check and an audit log. High-impact actions require human approval, and every use case ships with tests that are re-run on each change.

Is our data used to train AI models?

We configure providers so your data is not used for training wherever that option exists, and we can keep sensitive processing on infrastructure you control.

Other services

Have something in mind?

Tell us what you’re building — a new product, an AI feature, or a system that needs rescuing. We’ll reply with honest next steps.