Artificial Intelligence that fits your business, not the other way round
We build AI systems tailored to the workflows you already have. No rip-and-replace projects, no six-month timelines before you see a single result. Most clients have a working prototype within four weeks.
We hear the same stories from new clients. Here is what typically goes wrong and how we fix it.
The common problems
Off-the-shelf tools that need months of customisation before they produce anything useful.
Data scattered across spreadsheets, CRMs, and legacy databases with no clear pipeline.
Consultants who deliver a slide deck but never build the actual system.
Internal teams stretched thin, lacking ML engineering experience to move from experiment to production.
How we solve them
We audit your existing data in the first week and flag exactly what is usable today.
Prototypes ship in sprint cycles of two weeks, so you test real outputs, not mockups.
Every model we train runs on your own infrastructure or a UK-hosted cloud, keeping data under your control.
After launch we monitor model drift monthly and retrain when accuracy drops below agreed thresholds.
What we build
Each engagement starts from a specific business question, not a technology wishlist.
Predictive analytics
Demand forecasting, churn prediction, pricing optimisation. We connect to your transaction data and build models that refresh automatically on a schedule you choose, daily or weekly.
Document intelligence
Invoices, contracts, medical records. Our extraction pipelines pull structured fields from PDFs and scanned images with over 94% accuracy on English-language documents, validated against your own test set before go-live.
Process automation
We map your manual workflows, identify the steps that eat the most staff hours, and replace them with AI-driven automations. One logistics client cut order-processing time from 12 minutes to under 90 seconds per shipment.
Conversational AI
Customer-facing chatbots and internal knowledge assistants trained on your own documentation. We fine-tune language models so they answer in your brand voice, not generic boilerplate.
Four steps from idea to production
A clear timeline keeps everyone accountable.
Discovery audit
We spend three to five days reviewing your data sources, interviewing stakeholders, and defining the success metric. You receive a written scope document before any code is written.
Rapid prototype
Within two to four weeks we deliver a working model you can test against real inputs. Feedback loops are short: if the output is wrong, we adjust the same week.
Production deployment
The validated model moves into your live environment. We handle API integration, monitoring dashboards, and access controls. Typical deployment takes one to two weeks.
Ongoing support
Models degrade when the underlying data changes. We offer monthly retrain packages and quarterly performance reviews so accuracy stays above your agreed threshold.
94%
Average extraction accuracy
4 wks
Median time to first prototype
37%
Average cost reduction for clients
12
Models in production right now
Built by engineers, explained in plain language
Our team includes ML engineers, data architects, and a project manager who translates between technical detail and business goals. You will never sit through a meeting full of jargon without context.
We are based in London and work with clients across the UK and Europe. Remote collaboration is our default; on-site workshops happen when the project benefits from face-to-face whiteboarding, usually during the discovery phase.
Frequently asked questions
It depends on the task. For a classification model we typically want at least 1,000 labelled examples. For simpler rule-based automation, structured exports from your existing tools are often enough. During the discovery audit we assess exactly what you have and whether augmentation or synthetic data is needed.
Discovery audits start at £3,500. Full prototype-to-production projects range from £15,000 to £60,000 depending on complexity. We provide a fixed-price quote after the audit so there are no surprise invoices.
On infrastructure you control. We can deploy to your on-premise servers, a UK-region AWS or Azure account, or a private cloud instance. Data never leaves the jurisdiction you specify, and we sign a data processing agreement before any transfer.
Yes. About half our projects involve embedded collaboration with an in-house engineering team. We use your version control, CI/CD pipeline, and communication tools. Knowledge transfer is part of every engagement: your team should be able to maintain the system after we step back.
We define a minimum accuracy threshold during scoping. If the prototype does not hit it after two iteration cycles, we provide a detailed technical report explaining why and recommend next steps. You are not locked into further spend.
Ready to see what AI can do with your data?
Tell us about the problem you want to solve. We will respond within one working day with an honest assessment of whether AI is the right tool for it.
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Last updated: January 2026
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Disclaimer
Last updated: January 2026
The information on this website is intended as a general overview of Digital Savant AI's services. It does not constitute professional, legal, or financial advice.
Results described on this site, including accuracy percentages and cost reductions, reflect outcomes achieved for specific clients under specific conditions. Your results may differ depending on data quality, scope, and organisational factors.
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