We build AI tools you can actually use: models that forecast demand, systems that sort documents in seconds, and dashboards that surface the numbers your team needs before they ask.
Book a free discovery call
Most organisations collect more information than they can process. Spreadsheets pile up. Reports arrive too late. Here is what we see, and what we do about it.
Warehouse managers guess reorder quantities from gut feeling. Marketing teams run campaigns without knowing which channel actually brought last quarter's revenue. Customer service reps answer the same forty questions by hand, every day.
These are not technology problems at their root. They are information problems. The data already exists inside your ERP, your CRM, your email archives. It just sits there.
None of this requires ripping out existing systems. We connect to what you already run.
Four service areas, each scoped to produce measurable results within 90 days of kick-off.
Time-series forecasting for sales, inventory, churn, and cash flow. We train on your historical data, validate against hold-out sets, and deploy behind a simple API your existing tools can call. Most models reach production accuracy within three to four weeks of data ingestion.
Invoices, contracts, compliance forms: we train classifiers and extraction pipelines that pull structured fields from unstructured files. Output feeds directly into your accounting or case-management software through a webhook or scheduled batch job.
Fine-tuned large language models for internal knowledge bases, customer-facing chatbots, or content generation pipelines. We handle prompt engineering, retrieval-augmented generation setup, guardrail configuration, and ongoing evaluation so the model stays accurate as your data changes.
We connect AI outputs to the actions they should trigger: sending alerts, updating records, routing tasks. The glue layer runs on your existing cloud infrastructure, monitored with dashboards we hand over at project close. No vendor lock-in.
A clear four-phase engagement. Each phase ends with a deliverable you can evaluate before we move on.
We review your data sources, interview stakeholders, and identify the two or three highest-impact opportunities. This takes about a week and costs nothing.
A working prototype on a sample of your data, typically delivered within three weeks. You see real predictions or real extractions before committing to a full build.
We harden the model, write integration code, set up monitoring, and run parallel tests against your current process. Duration depends on scope but averages six to eight weeks.
Documentation, training sessions for your team, and a 90-day support window. After that, you can self-manage or keep us on a lightweight retainer for retraining cycles.
Dependable AI Systems started in 2019 when two machine-learning engineers grew tired of watching promising AI projects die in pilot purgatory. The pattern was always the same: a flashy demo, polite applause, then silence as the model never reached production.
We decided to focus exclusively on deployment. Every engagement has a defined production target, a timeline, and acceptance criteria agreed before work begins. If the proof of concept does not meet the bar, we stop and you owe nothing beyond the discovery phase.
Our team now includes seven people: three ML engineers, a data engineer, a DevOps specialist, a project lead, and a technical writer who produces the documentation your IT department will actually read. We are based in England and work with clients across the UK and Ireland.
We do not chase hype. When a simpler statistical method outperforms a deep neural network on your data, we say so and build the simpler thing. The goal is a system that runs reliably for years, not a slide deck that impresses for ten minutes.
It depends on the task. A demand-forecasting model typically needs 18 to 24 months of transactional history. A document classifier can work with as few as 200 labelled examples if the categories are well-defined. During the discovery audit we assess what you have and tell you honestly whether it is enough.
Both. About a third of our clients run everything on local servers for regulatory reasons. We deploy models as containerised services that run on any Linux host. Cloud deployments use Azure or AWS, depending on what you already have.
The discovery audit is free. A proof of concept runs between £4,000 and £12,000 depending on complexity. Full production builds range from £18,000 to £65,000. We quote fixed prices after the discovery phase so there are no surprises.
You do. All source code, trained model weights, and documentation are transferred to your repository at handover. We retain no proprietary claim. If you want to bring in another team later, they will have everything they need.
We sign a data processing agreement before any data leaves your environment. Where possible, we work inside your infrastructure so the data never moves. When transfer is necessary, we use encrypted channels and delete all copies within 14 days of project close. We are registered with the ICO and comply with UK GDPR.
Tell us what you are trying to solve. We will reply within one working day with an honest assessment of whether AI is the right tool.
Address:
85 The Fairway, Glover-upon-Gutkowski, England, OI4 7KU, United Kingdom
Phone:
+44 28 2023 4251
Email:
[email protected]
Office hours: Monday to Friday, 09:00 to 17:30 GMT.