We find your bottlenecks, build AI-powered automations, and keep them running — from document processing and invoice automation to contract review and data extraction. Start with a free AI readiness assessment.
The team at Winder.AI are ready to collaborate with you on your AI project. We tailor our AI solutions to meet your unique needs, allowing you to focus on achieving your strategic objectives. Fill out the form below to get started.
We sought AI engineering experts that could quickly learn our day-to-day scientific legal mapping processes enough to develop a tool to make our work more efficient. Winder.AI dug into our day-to-day workflow to thoroughly understand the value of an AI Assistant for scientific legal mapping, which is a critical process to the field of legal epidemiology.
Research shows that specialist-led AI implementation succeeds 67% of the time, compared to just 22% for DIY approaches. An AI readiness assessment identifies where automation will actually deliver — so you start with the workflow, not the technology.
Your team copies information between systems by hand. Every copy introduces errors, delays, and frustration. The work gets done, but it costs you five times what it should.
Invoices, claims, contracts, and correspondence sit in queues waiting for someone to read, extract, and route them. The backlog grows faster than your team can clear it.
You’ve tried off-the-shelf automation tools. They work for simple tasks, but the moment you need something specific to your industry or your processes, you hit a wall.
Most automation agencies build your workflows and walk away. We build them, run them, and take responsibility for the results. Our three-phase approach means you get a working system — not a prototype that gathers dust.
These are the specific types of work we build and run for our clients — from document intelligence and invoice automation to contract review and compliance reporting. Not a generic list of everything AI can do.
Extract structured data from invoices, contracts, claim forms, and correspondence using AI document processing. Route items to the right handler based on content, urgency, and rules specific to your business. Our clients process over 1,200 documents per month at 97% accuracy with full audit trails — replacing manual document scanning with intelligent document management. Learn more about our AI document processing services.
AI contract review that summarises incoming legal documents, flags key clauses, and identifies risks before a human reviewer sees them. Built for law firms, in-house legal teams, and compliance departments that need to process volume without missing detail.
AI invoice processing that matches payments against records, reconciles supplier invoices with purchase orders, and cross-references transaction data between systems. From invoice OCR to full financial reconciliation — catch discrepancies that manual checking misses.
Draft responses to routine enquiries — from residents contacting their council, tenants contacting their property manager, or customers contacting your service desk. Every draft goes through quality scoring before it reaches anyone.
Generate monthly compliance reports from operational data. Pull information from multiple systems, apply your reporting rules, and produce formatted outputs ready for review. Reduce a three-day reporting task to three hours.
Automatically classify incoming requests, emails, or documents and route them to the right team or workflow. Confidence-based routing means clear-cut items are handled automatically while edge cases get human attention.
Most AI automation agencies come from marketing backgrounds and focus on CRM workflows and chatbots. We come from AI engineering and focus on the harder problems — document intelligence, complex data extraction, and production-grade operations that actually run.
We specialise in AI document processing, contract review, and invoice automation — where accuracy, audit trails, and getting it right matter. We’ve delivered AI systems for Ofcom and built legal research automation for Temple University. You don’t need someone who understands AI. You need someone who understands your workflows.
Most agencies build your automation and walk away. We monitor, maintain, and improve it every month — with SLAs, human quality review, and incident response. Month six is better than month one because we continuously tune accuracy, prompts, and workflow logic.
No juniors, no handoffs. Every engagement is delivered by Phil Winder, PhD, author of the O’Reilly book on Reinforcement Learning, with over 12 years building production AI systems for organisations including Google, Microsoft, and Shell.
Every business has workflows buried in documents, emails, and spreadsheets. We specialise in turning that manual work into reliable AI-powered operations — whether you're processing invoices, reviewing contracts, or routing customer requests.
AI contract review, clause extraction, matter intake, and compliance monitoring. Built for law firms and in-house legal teams that need to process volume without compromising on accuracy. Learn more about AI in legal.
AI invoice processing, payment reconciliation, expense classification, and regulatory reporting. From invoice OCR to full accounts payable automation — we build workflows that maintain audit trails and route exceptions to human handlers. Learn more about AI in financial services.
Proposal generation, client onboarding, timesheet processing, and operational reporting. Any business that runs on documents and email can benefit from intelligent document management that routes, extracts, and processes information automatically.
Resident correspondence, planning application processing, FOI request handling, and compliance reporting. We understand public sector procurement and the specific accountability requirements of government operations.
We've delivered AI systems for some of the world's most recognised companies — and we bring the same engineering rigour to every engagement.
Case study
Winder.AI helped Duetto evaluate offline reinforcement learning for dynamic hotel pricing. Over five months, the engagement progressed from behavioural cloning baselines through Implicit Q-Learning experiments on real booking data, revealing where RL outperforms simpler approaches, what data quality prerequisites exist, and how to evaluate pricing agents when ground truth is unavailable.
Case study
Winder.AI helped Apartment List modernize its machine learning operations by unifying data pipelines, automating Kubeflow workflows, and introducing enterprise-grade governance. The outcome: consistent training and inference data, faster deployment cycles, and self-service capabilities that enabled Apartment List’s data science team to scale model delivery with confidence.
Case study
Using digital twin data to build flight traffic simulators and train reinforcement learning AI agents. A leading aerospace business and Winder.AI opened new horizons for dynamic, data-driven scheduling solutions that integrate with our client’s advanced flight planning technology.
LLM
A firm asked me what it would cost to generate a long technical report with AI, end to end, on Microsoft’s stack. Their documents run to a couple of hundred pages, written to a method the firm has refined over years, and that method is what clients pay for. So I spent a day pricing it properly, per document, in every place Microsoft will let you build such a thing.
One document came to $725 on Copilot Studio and about $4 calling Azure’s own model API. Both numbers are Microsoft’s, on the same tokens, on the same day. The gap is not a markup. It is the price of a bundle, and on this particular job you pay for all of the bundle and can use almost none of it.
LLM
In August our Helix fleet was serving Qwen3.8-27B to its coding agents on eight NVIDIA RTX PRO 6000 cards, one SGLang engine per GPU, and every engine stopped at 12 running requests. SGLang had sized the cache that holds each request’s recurrent state when it started, capped itself to fit, and printed “max_running_requests is capped to 12 by the mamba state cache” at every boot. Nobody had noticed. Storing that state in bfloat16 doubled the slots, and throughput at 192 concurrent requests rose from 3,833 to 7,883 tokens a second (HelixML). A month later our own benchmark on a single H100 hit the same cap.
vLLM and SGLang are GPU inference servers built to run many requests at once, vLLM around PagedAttention and SGLang around RadixAttention. TensorRT-LLM is NVIDIA’s server for NVIDIA GPUs. llama.cpp runs quantised GGUF models on CPUs, Apple silicon and GPUs, and Ollama wraps it, since June 2026, in a one-command local server.
Machine Learning
In April 2011, a developmental-biology textbook about flies was listed on Amazon for $23,698,655.93, plus $3.99 shipping. Two booksellers’ pricing bots were pricing against each other. One set its price at 0.998 times its rival’s, the other at 1.27 times the first. The two rules multiply to more than one, so the price ratcheted up daily until a biologist noticed.
You can build a pricing algorithm that would never ask $23.7 million for a biology textbook. The common two-stage build, where you train a model to predict demand and then charge the price the model likes best, is no protection at all. What works is sequential decision making: dynamic programming and reinforcement learning, the ground I have spent most of the last decade on and wrote O’Reilly’s book about.
Common questions about our AI automation services. If your question isn't covered here, book a call and we'll answer it directly.
Our audit starts at £2,000 and is designed for businesses from 10 employees upward. The ongoing Run phase uses usage-based pricing, so you pay more when volumes are high and less when they’re not. You don’t need a large IT budget to get started.
Yes. We build on platforms like Make and n8n, which connect to over 400 business tools including Microsoft 365, Google Workspace, Salesforce, Xero, and most CRM and ERP systems. If your system has an API, we can connect to it.
Your data stays yours. We sign data processing agreements, never use your data to train AI models, and can host workflows on UK infrastructure if required. For regulated sectors, we design workflows with full audit trails so you can demonstrate compliance.
Every workflow includes confidence thresholds and quality checks. When the AI is uncertain, items are routed to human review. We monitor accuracy continuously and take responsibility for the outputs our managed workflows deliver. This is what separates production-grade automation from a prototype.
Yes, and we recommend it. The audit identifies the best starting point — typically the process with the highest volume of manual work and the clearest rules. We implement that single workflow first, prove the value, then expand.
The audit is a standalone engagement with no further obligation. Implementation projects are fixed-scope and fixed-price. Run retainers have a three-month minimum with 90-day notice after that. There are no long-term lock-ins.
No. That’s the point. We manage everything — the AI models, the workflow infrastructure, the monitoring, and the ongoing optimisation. You interact with us through regular reports and a shared dashboard, not through code.
Our audit starts from £2,000 for smaller businesses and typically runs £5,000–£15,000 for more complex operations. Implementation starts from £5,000 per workflow, with multi-system integrations typically £12,000–£30,000. Ongoing management starts from £500 per month plus usage-based pricing tied to your volume. Visit our pricing page for more detail.