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Engineering services

Build, integrate and harden the systems around AI

Neul Labs Limited is a founder-led UK software company. We combine the engineering practices behind our public open-source portfolio with scoped technical delivery for vendors, startups and product teams.

What we can deliver

Every engagement starts with a narrow outcome and an evidence plan. We do not claim platform affiliation, certification, customer results or production readiness unless the relevant evidence exists.

AI agent systems engineering

Architecture, prototypes and production hardening for agent workflows, tool use, memory, human approval, evaluation and operational controls.

Typical outputs

  • Reference architecture and delivery plan
  • Working integration or proof of concept
  • Evaluation, observability and handover documentation
Capability, method and fit →

Performance engineering

Profiling and optimisation for Python, Rust and mixed-language systems, including PyO3 acceleration, concurrency, persistence and workload-specific benchmarks.

Typical outputs

  • Reproducible baseline and bottleneck report
  • Prioritised implementation with measured trade-offs
  • Benchmark harness and regression checks
Capability, method and fit →

Platform and API integrations

Customer-authorised integrations across cloud, data, commerce, lifecycle, customer-experience and developer platforms, with least-privilege access and maintainable operations.

Typical outputs

  • Scope and data-flow map
  • Secure integration with test and rollback paths
  • Install, support and deprecation runbook
Capability, method and fit →

Open-source and developer tooling

SDKs, CLIs, automation, compatibility layers and maintainable open-source components for vendors and engineering teams.

Typical outputs

  • Product and interface design
  • Tested implementation and release workflow
  • Documentation, examples and maintainer handover
Capability, method and fit →
R&D collaboration

Turn technical uncertainty into a bounded experiment

Neul Labs can contribute a defined software work package to an internal R&D programme, academic collaboration or eligible consortium. The work begins with a knowledge gap and experimental decision, not a funding programme name.

Review the engineering evidence method →

Research question

Define the technical uncertainty, current baseline, variables, success and a useful negative outcome.

Experimental software

Build the smallest instrumented prototype, harness or integration needed to answer the question.

Reproducible evidence

Retain versions, methods, raw observations, costs, failed approaches, uncertainty and limitations.

Consortium work package

Agree inputs, outputs, IP, security, dependencies, budget, reporting and exploitation ownership with the lead.

A capability page or proposal does not establish eligibility, grant award, research-partner status or match finance. Those claims require the call rules, consortium and written funder decision for the specific project.

Delivery model

Evidence before scale

  1. 1

    Scope

    Name the outcome, constraints, owners, data, success measures and support boundary.

  2. 2

    Prove

    Use synthetic or customer-authorised data, reproducible tests and a small reversible deployment.

  3. 3

    Harden

    Add security, privacy, observability, failure handling, cost controls and operational documentation.

  4. 4

    Handover

    Transfer source, tests, runbooks and decision records with explicit maintenance ownership.

Engagement boundaries

Services are scoped by written agreement. Public repositories and website content are not a warranty, service-level agreement or substitute for project-specific review.

We start integrations with synthetic data and least-privilege access. Customer, employee, communications, advertising, payment or regulated data is used only with appropriate authority and controls.

Vendor names may describe technical compatibility or a proposed integration. They do not imply endorsement, certification or partner status. We publish those claims only after the provider awards them.

Send a scoped enquiry →

Have a specific system to build or improve?

Tell us the desired outcome, current stack, constraints and target timeline. We will respond with the smallest useful next step.

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