We build intelligent systems for ambitious organizations.

LT Lab helps companies connect their systems, automate operations, engineer reliable data platforms and build AI-powered digital products that solve real business problems.

Capabilities: Generative AI, AI Agents, Data Engineering, Odoo, Zoho, Integrations, Platforms, Automation.

What we do

00 — The starting point

Technology should make the business simpler, not more complicated.

Organizations often accumulate disconnected applications, spreadsheets, databases and manual processes.

01 — Integrate

Integrate

Connect the systems your business already depends on.

LT Lab helps bring these systems together, so a record is created once and every tool sees the same truth.

02 — Automate

Automate

Replace repetitive workflows with intelligent automation and AI agents.

Invoices reconcile themselves, inboxes triage themselves and reports refresh overnight.

03 — Build

Build

Engineer reliable platforms, applications and data infrastructure around your operations.

We design the infrastructure, integrations, data pipelines, intelligent applications and automation required to turn fragmented operations into connected digital systems.

Capabilities

From AI experiments to production infrastructure.

Six connected disciplines, delivered by one engineering team, so AI, data, integrations and software are designed to work together.
All services

Build practical AI applications around organizational data and workflows.

  • Generative AI applications
  • Enterprise knowledge assistants
  • Retrieval-Augmented Generation
  • Private knowledge bases
  • LLM integrations
  • AI search
  • Document intelligence
  • Custom copilots
Explore AI

From fragmented systems to intelligent infrastructure.

AI that works

Move AI from demonstration to deployment.

LT Lab works with organizations to identify where generative AI and intelligent agents can create measurable operational value.

Instead of adding another standalone chatbot, we connect AI directly to the organization's data, workflows and existing software.

Grounded
Answers come from your approved sources, with citations.
Permission-aware
People only see what they are already allowed to see.
Connected
Agents act in your CRM, ERP and inbox, with human review.
Explore AI solutions
Knowledge assistantillustrative

Illustrative example of an AI knowledge assistant.

Question: A client on an enterprise plan is asking for a refund 45 days after invoicing. What does our policy allow, and can you prepare the reply?

Sources retrieved: Refund_Policy_2026.pdf, §4.2 Enterprise refunds; Enterprise_Agreement.docx, §11 Cancellation; Zoho Desk macro, Refund request · enterprise.

Answer: Enterprise refunds are available within 60 days of invoicing if the service hasn't been activated [1]. Requests after 30 days need finance approval before we confirm [2]. I've drafted a reply from the approved template [3] and routed it for approval.

Agent actions: Draft reply created in Zoho Desk; Approval task assigned to Finance in Odoo; Waiting for human review before sending.

Systems touched: CRM, ERP, Email, Documents, APIs.

Company Data → Knowledge Layer → AI Model → AI Agent → Business Systems. Select a layer to replay from it.

Connected systems

Make your software work together.

Businesses often run critical operations across multiple tools. We connect these systems so information can move automatically, accurately and securely.
Discuss an integration

LT Lab Integration Layer

Mapping · Validation · Queues · Monitoring

Hover or select a system to see a typical data flow.

Our work

Built around real operational problems.

Representative solutions that show the kinds of systems we design and deliver. Each starts with an operational problem, not a technology.
View all work

01 / 06: Unified Operations Platform

Data infrastructure

Build the foundation your analytics and AI actually need.

AI and analytics are only as reliable as the systems underneath them.

We design pipelines, warehouses and data platforms that make organizational information dependable, accessible and ready for decision-making.

reference_architecture / data_platform

Scheduled · Tested · Monitored

  1. 01

    Sources

    • APIs
    • ERP
    • CRM
    • Files
  2. 02

    Ingestion

    • Airflow
    • Connectors
    • Streaming
  3. 03

    Transformation

    • dbt
    • SQL
    • Python
    • Tests
  4. 04

    Warehouse / Lakehouse

    • PostgreSQL
    • Cloud
  5. 05

    Analytics + AI

    • Power BI
    • AI Models
Data flows through Sources, then Ingestion, then Transformation, then Warehouse / Lakehouse, then Analytics + AI.

Last night's run

Every stage is scheduled, tested and observable, so problems surface before anyone opens a dashboard.

illustrative

  1. 02:00ingest_erp_orders✓
  2. 02:01ingest_crm_deals✓
  3. 02:02ingest_payments_api✓
  4. 02:04dbt build✓
  5. 02:06data tests✓
  6. 02:06freshness check✓
  7. 02:07refresh dashboards✓

APIs · ERP · CRM · Files · PostgreSQL · Airflow · dbt · Cloud · Power BI · AI Models

Build your data platform

Digital products

When off-the-shelf software isn't enough.

Some workflows are too specific for generic software.

LT Lab designs custom platforms around the way organizations actually operate, from internal systems and client portals to SaaS products and operational applications.

  • Product strategy
  • UX architecture
  • Frontend engineering
  • Backend engineering
  • Database design
  • API development
  • Authentication where required
  • Cloud deployment
  • Monitoring
  • Continuous improvement
Build a platform

Our approach

Start with the problem. Engineer the right system.

  1. 01 —

    Understand

    We map the workflows, systems, data and business objectives.

    • + Stakeholder workshops
    • + Process and system mapping
    • + Data assessment

    Problem definition and priorities

  2. 02 —

    Architect

    We design a technical approach around the organization's existing environment and future requirements.

    • + Solution architecture
    • + Technology selection
    • + Delivery plan

    Architecture and roadmap

  3. 03 —

    Build

    Our engineers develop, integrate and test the solution iteratively.

    • + Iterative sprints
    • + Integration and testing
    • + Regular demos

    Working, tested software

  4. 04 —

    Improve

    We deploy, monitor and continue optimizing the system as the organization grows.

    • + Deployment
    • + Monitoring and support
    • + Continuous improvement

    A system that keeps getting better

Engineering stack

Modern technology. Chosen for the problem.

We are pragmatic about tools. The right choice depends on your environment, your team and what you need to maintain after launch.
01AIModels and frameworks for applied AI
OpenAIAnthropicGeminiLangChainLlamaIndexVector Databases
02DataPipelines, modelling and storage
PythonSQLPostgreSQLAirflowdbtKafka
03Business SystemsOperational platforms we integrate
ZohoOdooMicrosoft 365Google Workspace
04PlatformsApplication engineering
Next.jsReactTypeScriptNode.jsFastAPIREST APIs
05CloudInfrastructure and deployment
AWSAzureGoogle CloudDocker
Two software engineers reviewing code together on a laptop in a busy open-plan office

Built in Africa

Engineering locally. Building globally.

LT Lab combines local business understanding with modern software, AI and data engineering practices.

We work with organizations that need reliable technology built around real operational challenges, whether the system serves one office, multiple countries or a global customer base.

Local understanding
Context on how organizations in the region operate, transact and grow.
International practice
Modern engineering, security and delivery standards on every project.
Built to scale
Systems that serve one office, several countries or a global customer base.
About LT Lab

Insights

Thinking about AI, data and modern systems.

Start a conversation

Have a system that needs to work better?

Whether you're exploring AI, connecting business systems, rebuilding your data infrastructure or developing a new platform, we'd like to understand the problem.

Project inquiry

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Share a few details about the problem, the systems involved and your timeline. We'll come back with questions, initial thoughts and suggested next steps.

  • A real conversation

    An engineer reads every inquiry — not an automated sales sequence.

  • A timely reply

    We aim to respond within two working days.

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