Washington DC, engineering since 2009
Ainsworth Lloyd designs, builds and deploys AI systems, custom software and the infrastructure underneath them. Seventeen years of delivery for federal agencies, health systems, financial institutions and technology companies.
Organisations our team has delivered into, directly or through partners. Client names and engagement outcomes are shared under NDA rather than published.
Position
Ainsworth Lloyd is an engineering firm. We combine applied AI research, software architecture, product design and process automation into systems that carry real operational load.
The ones that route the claim, price the risk, schedule the fleet, read the document and answer the citizen. Built to be inspected, tested and handed over.
Capabilities
Most engagements use three or four of these at once. They are separated here for clarity, not because they ship separately.
Agents, retrieval, vision and forecasting, wired into the systems that already run your business.
Every engagement starts with a measurable outcome and an evaluation set. If a deterministic rule beats a model, we ship the rule and say so.
Systems built for one organisation and one problem, modelled properly rather than configured badly.
Domain modelling, a real test suite, written architecture decisions, and a handover that includes the keys and the runbook.
Native iOS and Android, Flutter and React Native, built offline first and secure by default.
Shipped through the stores and kept there, with crash budgets, staged rollout and the release process documented.
Platforms, portals and public surfaces that hold up under load, audit and a screen reader.
Accessible to WCAG 2.2 AA, measured against Core Web Vitals, and shipped behind a rollout you can reverse.
Process automation that removes the queue, not the person who understood it.
Approvals, exceptions and audit trails designed in from the first diagram, so the automated path is the accountable one.
Multi-tenant systems with identity, billing, reporting and the integrations procurement will ask about.
Built to pass a security review, an accessibility review and the next ten years of maintenance by someone else.
AI systems
We build AI that sits inside an operational process and is accountable for an outcome. Every system ships with an evaluation set, a fallback path and a plain statement of what it cannot do.
Multi-step agents with real tool access, bounded scope and an approval gate on anything that leaves the building.
Detection, classification and document understanding on images, video and scanned records.
Drafting, summarisation and synthesis, grounded in your sources and cited back to them.
Models placed inside a workflow where they beat a rule, and rules kept where they beat a model.
Ranking and personalisation trained on your data, measured against a holdout, not a demo.
Systems that show the evidence behind a recommendation so a person can accept or overrule it.
Model routing, cost and latency budgets, caching and graceful degradation across providers.
Tenant isolation, data residency, audit logging and human review, designed in from the start.
Software engineering
Not a prototype that needs a real team afterwards. Interface, service, data, infrastructure and the operational work that keeps them running.
Mobile and web
A single domain model behind an application that behaves natively on a phone, correctly on a desktop and predictably offline. Designed together, shipped together.
Throughput
18,402
Median latency
212ms
Queue depth
7
Today
1,284
records processed
Awaiting approval
Swift and Kotlin where the platform matters, Flutter and React Native where velocity does.
Server rendered, streamed, and fast on the hardware your users actually own.
Installable, offline capable, and updated without an app store review.
Shared contracts and one source of truth, so the surfaces never disagree.
How we work
The same six stages whether the engagement runs six weeks or three years. Each one produces something you can read.
We map the process as it actually runs, not as the documentation describes it, and agree what success will be measured against.
Written architecture decisions, a data model, an integration plan and a cost envelope, before anyone writes production code.
Short increments against a working system. Tests, review and a deployable trunk from the first week.
Identity, payments, records and the systems you already depend on, connected behind contracts that are versioned.
Staged rollout behind flags, with monitoring, alerting and a rollback that has been rehearsed.
Capacity, cost and reliability tuned against real traffic, then handed over with the runbook.
Technology
A capability is only worth listing if it connects to the others. Intelligence needs somewhere to run, engineering needs something to reason over, and a platform is what keeps both accountable.
Selected work
Sector, system and stack. Client names and outcomes are shared under NDA in conversation rather than published here.
A legacy caseload system replaced in place: the same records, the same statutory rules, a new service boundary and an interface a caseworker can actually move through.
Scanned records read, structured and reconciled against the patient index, with every extracted field traceable back to the pixel it came from.
Position and exposure recomputed continuously rather than overnight, so the number on the desk and the number in the report are the same number.
Routing and allocation moved from a spreadsheet and a phone call to a solver that explains its assignment and lets a dispatcher override it.
Why Ainsworth Lloyd
We are measured on whether the thing works in production, not on whether the sprint closed. That changes what gets built.
A written decision record, a data model and a cost envelope come first. Most expensive failures are architectural and arrive early.
Deterministic logic is cheaper, faster and testable. We use models where they beat it, and we show you the comparison.
Federal procurement, clinical governance and financial audit. We build to survive the review, not to pass a demo.
Source, infrastructure, credentials, documentation and a runbook. No dependency on us that you did not choose.
The firm predates this wave of AI and will outlast the next one. We have replaced our own work more than once.
Start here
Tell us what you are trying to build, automate or transform. You will speak to an engineer, and you will leave the first conversation with an opinion about your problem whether or not you hire us.
