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Services Modulus Labs AI

AI systems, and the software around them.

We design, build and run production AI for companies in the US, the UK, Europe and the Gulf: AI agents, knowledge systems and automation, and the web and mobile apps people use them through.

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AI systems
Agents · LLM & RAG · Automation · Integration · Evals & security · Strategy
Software
Web development · Mobile apps · Custom software
Industries
Healthcare · Insurance · Finance · Legal · Real estate · Retail · Logistics · Manufacturing · Construction · Hospitality · Education · and more
Markets
United States · United Kingdom · Europe · UAE · Saudi Arabia · Pakistan
Ways to engage
Project · Embedded team · Advisory
Reply time
Within one business day

01 AI systems

Built for production, not the demo.

Every system ships with an evaluation set, guardrails, fallbacks and monitoring, because that's what keeps a model useful after launch day.

Fig. 1 An agent's steps, each one checked
  1. 1.1

    AI agents

    Agents that work inside your CRM, ERP, ticketing and WhatsApp. They answer, qualify, quote, book and update records within limits enforced in code, and hand over to a person when they should. Our WhatsApp sales agent handles 70% of a solar company's monthly sales.

  2. 1.2

    LLM applications and RAG

    Assistants and search over your own documents, with hybrid retrieval, reranking and citations, and the judgement to say "I don't know" when the evidence is weak. How we build retrieval.

  3. 1.3

    AI workflow automation

    Document-heavy, repetitive work automated with human checkpoints and an audit trail: reading, checking, routing and drafting, integrated with the systems your team already uses.

  4. 1.4

    Integration and deployment

    AI built into the products and systems you already run, shipped with release pipelines, rollback and production alerting from the first day.

  5. 1.5

    Evaluation and AI security

    Evaluation sets and release gates, prompt-injection defense, PII and access controls, and AI-specific security reviews, for systems we build and systems you already run. Evals before features.

  6. 1.6

    AI strategy

    Use-case discovery ranked by return, architecture and model choices, build-or-buy decisions, and a roadmap your team can actually deliver. We'll tell you when AI isn't the right tool.

02 Software

The software around the model.

  1. 2.1

    Web development

    Fast, accessible websites and web applications. Built to load fast, read well on every screen and rank in search.

  2. 2.2

    Mobile apps

    iOS and Android apps for customers and field teams, including the AI features inside them: assistants, document capture and smart search.

  3. 2.3

    Custom software and integrations

    Internal tools, dashboards, APIs and the connections between your systems, so data moves without anyone retyping it.

03 Industries

Where our systems run.

In production in healthcare, legal, energy, fintech and real estate, and built for any business where work runs on documents and conversations.

04 Where we work

Built for the rules where you operate.

A US company working with teams across North America, Europe and the Middle East.

  1. 4.1

    United States

    Production AI for US companies, designed for HIPAA where health data is involved and for the state rules on automated decisions. How we compare.

  2. 4.2

    United Kingdom and Europe

    Systems built for UK GDPR, the EU AI Act and Italy's national AI law, with documentation and human oversight built in. The EU AI Act in 2026 · AI rules in the UK.

  3. 4.3

    UAE and Saudi Arabia

    Arabic and English assistants and WhatsApp agents, designed for federal and free-zone data rules and in-Kingdom hosting. The UAE · Saudi Arabia.

  4. 4.4

    Pakistan

    AI agents, automation and software for Pakistani businesses, from solar to retail. AI companies in Pakistan.

05 How we work

Measure first, then build.

Every engagement moves through the same four stages, whatever its size.

  1. 01

    Discovery

    We map the workflow, the data and the risks, agree what success means in numbers, and build the evaluation set first.

  2. 02

    Build

    Small, reviewed increments, each scored against that evaluation set before it merges.

  3. 03

    Deploy

    Release pipelines with rollback, guardrails on every path in and out, and monitoring from day one.

  4. 04

    Operate

    We watch quality, latency, cost and drift in production, and keep improving the system after launch.

Ways to work with us

  • Project

    A defined system, built end to end against agreed success criteria, then handed over with its runbooks.

  • Embedded team

    Our engineers inside your team, shipping alongside your people and leaving them stronger.

  • Advisory

    Architecture, reviews and build-or-buy decisions on a fractional basis, without a full build.

06 Questions

What buyers ask us first.

  1. 6.1

    How does a project start?

    With a conversation about the problem, then a short discovery: the workflow, the data, the risks and the number that defines success. You get a plan and an estimate before any build.

  2. 6.2

    How long does a project take?

    A focused system usually reaches production in six to ten weeks; larger integrations take three to five months. Discovery comes first, so you see the plan before any build.

  3. 6.3

    Who owns what we build?

    You do: the code, prompts, evaluation sets, infrastructure and documentation. When we hand over, your team can run and extend it.

  4. 6.4

    Can you work with our team and our time zone?

    Yes. We work with teams across the US, Europe and the Middle East, with overlapping hours for stand-ups and reviews, and we can embed alongside your engineers.

  5. 6.5

    Which models do you use?

    Whichever passes your evaluation set at the right cost: models from OpenAI, Anthropic and Google, or open-weight models on your own infrastructure. We keep the model replaceable.