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Delta AI Engineering

Intelligence for a brighter tomorrow

Production AI, engineered for measurable change.

We design, build and operate agentic systems, retrieval platforms and the cloud engineering beneath them. Every engagement starts with a baseline and ends with evidence.

Start a projectSee how we work
  • PEOPLE
  • TECHNOLOGY
  • SOLUTIONS
  • IMPACT
01Retrieve
02Reason
03Act

What we build

Six capabilities, one standard of evidence.

From the first architecture decision to the dashboard that proves the system still works.

  • Agentic systems

    Multi-agent workflows that plan, call tools and hand off to people at the right moment, built on explicit state so every step can be inspected.

  • Retrieval and knowledge

    Grounded answers from your own documents using hybrid search, semantic reranking and citations people can check.

  • Cloud and platform engineering

    The foundation AI runs on: containerised services, CI/CD, infrastructure as code and observability from the first commit.

  • Evaluation and LLMOps

    Measure quality, latency and cost continuously so model or prompt changes ship on evidence instead of intuition.

  • Applied data science

    From raw records to decision-ready reporting, with modelling choices explained in language your stakeholders can act on.

  • AI strategy and architecture

    A short, structured engagement to decide where AI earns its place, what to build first and what it should cost to run.

Quality · Latency · Cost

Every AI system is a trade-off. We make it explicit.

Move the marker to see how priorities change the architecture. In a real engagement these budgets are agreed in writing and tracked like any other requirement.

Drag the marker, or choose a priority below.

Priority
Model
Mid-tier model with routing to a larger model for hard cases
Retrieval
Hybrid retrieval (≈25 candidates) with reranking
Caching
Prompt caching on shared context
Oversight
Sampled human review with drift alerts

Illustrative design heuristics. Real choices are set by your evaluation results and budgets.

Grounded answers

Answers that show their sources, or admit they have none.

Hybrid retrieval finds candidates by keyword and meaning. A reranker scores each passage against the question. Only passages that clear the bar reach the model, and every claim is cited.

Question

How long do customers on annual plans have to request a refund?

Grounded answer

Annual-plan customers can request a full refund within 30 days of purchase or renewalsource 1. After that, cancellation stops the next renewal but the current term is not refundedsource 2.

  1. [1] Refund policy v4, section 3.2: annual plans
  2. [2] Terms of service, section 9: cancellations

If no passage clears the threshold, the system says it does not know.

Illustrative example with sample documents.

The Delta Method

Five stages. Each one answers a question and leaves evidence behind.

Stage 1 of 5

What change should this system produce, and how will we measure it?

We map the workflow, the people in it and the data behind it, then agree a baseline and a success metric before any model is chosen.

Leaves behind

Outcome brief with baseline metric

Read the full approach

Principles

  • 01

    Measured, not assumed

    Every engagement starts with a baseline and ends with a comparison against it.

  • 02

    People stay in control

    Consequential actions pause for human approval. Automation earns autonomy gradually.

  • 03

    Explicit over clever

    State machines, typed contracts and written decisions make systems easier to trust and to change.

  • 04

    Budgets are features

    Quality, latency and cost targets are agreed up front and tracked like any other requirement.

Tell us the change you need. We will tell you how we would measure it.

A short first conversation, a written summary afterwards, no obligation.

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