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Exposys

Intelligence ยท AI Solutions

AI solutions that know your business, not just the internet.

We design and build AI features that work on your own documents, data and processes, from internal assistants to document extraction and prediction. Every system is evaluated against real examples before launch and designed so sensitive data stays under your control.

01Problems we solve

If this sounds familiar, we can help.

  • Knowledge locked in documents

    Policies, contracts and past work exist, but staff spend hours searching for the right answer.

  • Manual reading and data entry

    Teams copy details from invoices, forms and emails into systems by hand, one document at a time.

  • Pilots that never ship

    A chatbot demo impressed everyone, but nobody trusts it enough to put it in front of customers.

  • Worries about data and risk

    Leaders want the benefits of AI without sending confidential information to unknown places.

02What we build

AI features scoped to a real task, measured against real examples.

  • 01

    LLM assistants and copilots

    Internal or customer-facing assistants that answer questions, draft replies and follow your tone and rules.

  • 02

    RAG over company knowledge

    Search and question answering grounded in your documents, with citations so people can check the source.

  • 03

    Document understanding

    Extracting structured fields from invoices, contracts, forms and reports, with review steps where accuracy matters.

  • 04

    Classification and prediction

    Routing tickets, tagging content, scoring leads or forecasting demand from the data you already hold.

  • 05

    AI inside existing products

    Adding summarisation, smart search or drafting to your web app, portal or internal tools through clean APIs.

  • 06

    AI readiness and evaluation

    Assessing where AI fits, testing an existing system against your examples and recommending what to change.

03Key capabilities

The craft behind every release.

  • Retrieval-augmented generation
  • Prompt and output design
  • Structured data extraction
  • Evaluation sets and testing
  • Embeddings and vector search
  • Guardrails and content filtering
  • Usage, cost and latency monitoring
  • Privacy-aware data handling

Technology we use

  • OpenAI API
  • Anthropic Claude
  • Llama
  • Mistral
  • Python
  • LangChain
  • LlamaIndex
  • pgvector
  • PostgreSQL
  • FastAPI
  • Hugging Face
  • AWS

04How we work

A clear path from first call to handover.

  1. 1

    Find the use case

    We pick one task with clear value, collect real examples and agree what a good answer looks like.

  2. 2

    Prototype and evaluate

    A working prototype on your data, scored against a test set so quality is measured, not guessed.

  3. 3

    Build for production

    Integration with your systems, access controls, logging, guardrails and a review step where needed.

  4. 4

    Monitor and improve

    We track quality, cost and usage after launch and refine prompts, retrieval or models as you learn.

What you get

Concrete deliverables, agreed in writing before work starts.

  • Use case assessment and priorities
  • Data and privacy review
  • Evaluation set built from your examples
  • Working prototype on your data
  • Model and provider recommendation
  • Retrieval and document ingestion pipeline
  • Production API or user interface
  • Guardrails and human review steps
  • Logging, monitoring and cost tracking
  • Responsible AI and usage guidelines
  • Technical documentation and handover
  • Post-launch tuning period

05Why Exposys

One senior team, accountable end to end.

  • Evaluation before enthusiasm

    We test against your real cases and show you where the system is strong and where it still needs a person.

  • Model-agnostic choices

    We compare hosted models from OpenAI and Anthropic with open models, and pick on quality, cost and data needs.

  • Privacy designed in

    Data minimisation, access controls and provider settings chosen so confidential information is handled deliberately.

  • Humans stay in charge

    Where decisions carry risk, the AI suggests and a person approves, with a clear record of both.

Who it's for.

  • Professional services

    Searching precedents, policies and past proposals, and drafting first versions faster.

  • Finance and operations

    Reading invoices, statements and forms, and flagging items that need attention.

  • Customer support

    Suggested replies and knowledge search grounded in your help content and history.

  • Education and training

    Course assistants and content tools that stay within approved material.

06FAQ

AI Solutions questions.

Will our data be used to train someone else's model?

We configure providers so your data is not used for training where that option exists, and explain each provider's terms before you choose. For stricter needs we can use open models hosted in your own cloud account.

How do you stop the AI from making things up?

We ground answers in your own documents, ask the model to cite its sources and test against a set of real questions. No model is perfect, so for higher-risk tasks we add a human review step rather than pretend the risk is zero.

Which model should we use?

It depends on the task, the sensitivity of the data and the cost per request you can accept. We usually test two or three options against your examples and recommend one with the evidence in front of you.

Do we need a lot of data to start?

Often not. Assistants and document tools can work from the documents you already have, while prediction models need enough historical records, which we check during the assessment.

Can you improve an AI system someone else built?

Yes. We start by evaluating it against your real cases, find where it fails and why, and then fix retrieval, prompts, data or model choice as needed.

Start a project

Have a task AI could take on? Let's test it properly.

Tell us what you are building. We will reply with clear next steps and honest advice, even if we are not the right fit.

contact@exposysglobal.com