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Machine Learning & GenAI
From demand forecasting to document understanding and generative product features, we build ML systems with the evaluation, deployment and monitoring they need to stay accurate.
We scope this service around your workflow, existing systems and acceptance criteria. The work starts with the problem and its constraints, then a written scope and price. A packaged solution is a different buying route: choose it when its defined deliverables already fit the job.
01The problem
Predictive models and generative features built, tested and deployed like production software.
Models trained on last year's data degrade quietly once real users arrive.
Teams ship a prompt and hope. Nobody can say whether the output got better or worse this week.
Models sit in notebooks because nobody built the API, the interface or the retraining job around them.
02Capabilities
Forecasting, scoring, classification and recommendation models trained on your data.
Extraction, summarisation and classification for contracts, invoices, forms and support tickets.
Assistants, drafting tools and search built into your product rather than bolted beside it.
We choose retrieval, fine-tuning or both based on accuracy, cost and how often your data changes.
Golden datasets and automated scoring, so every model or prompt change is measured before release.
Image classification, OCR and visual inspection where cameras and scans hold the data.
03Outcomes
A comparison against a baseline using representative examples from the actual task.
Retrieval, citations and refusal behaviour designed around the information users may access.
Versioned evaluations show how a model or prompt change affects the cases that matter.
04Approach
Agree the task, acceptable errors, business constraints and a non-AI baseline.
Review data rights, labels and difficult cases, keeping evaluation examples separate from development data.
Compare retrieval, prompting, fine-tuning or a predictive model against the same acceptance criteria.
Connect inference to the product, track quality and cost, and hand over reproducible checks and rollback steps.
05Stack
06Case studies
“Distil Stack approached our education platform as a complete learning and business management solution. Their understanding of course delivery, instructor workflows, enrolments, certifications, and administration helped shape a system built around both student experiences and operational needs.”
TechFiosClient organisation
“Distil Stack approached the workout timer with a clear focus on functionality and user experience. Their attention to the details of interval training and timing interactions helped shape an application designed to be practical and intuitive during real workouts.”
AppRebel, Inc.Client organization“Distil Stack understood the operational demands of managing restaurant employees and developed a solution focused on the details that matter—attendance, shift allocation, working hours, and salary administration. Their approach connected technology with practical workforce management.”
Pepe’s Piri PiriClient organisation“Our goal was to make personalized learning more accessible to students through technology. Distil Stack understood the educational vision behind Baseet Teacher and approached the product as a complete learning experience, connecting AI tutoring, exam preparation, interactive study tools, and student engagement.”
Abdulsalam AlrehailiFounder & CEO
“Our operations involve much more than booking a moving job. Distil Stack approached the platform with a clear understanding of dispatch, drivers, foremen, customers, and payments, creating a connected system designed around the way our business actually operates.”
Bakhtier AzizbekovFounder & CEO
“Distil Stack understood the challenges of building a financial platform where trust, transparency, and user experience are essential. Their ability to translate complex lending and repayment workflows into a structured digital experience aligned with our vision of making financial support between friends and family simpler and more accessible.”
Dennis CailCEO & Co-founder
“Distil Stack understood the importance of creating a digital experience that feels approachable while supporting a meaningful wellness journey. Their work focused on bringing together the technology and user experience needed for a sleep-focused platform.”
Polly RevalienteCompany representative
“Distil Stack understood that building a platform for aviation requires more than a conventional application. Their approach focused on translating a specialized business concept into a practical digital product, with careful attention to usability and the needs of different users.”
Isaac NsubugaFounder & CEO
“Our platform needed to make invoicing and financial administration straightforward without overlooking important business requirements. Distil Stack approached the solution with an understanding of usability, operational workflows, and the importance of reliable financial processes.”
PatrickFounder
“Distil Stack demonstrated a strong understanding of the complexity behind a specialized medical education platform. They helped bring together question banks, assessments, resident programmes, rankings, and performance tracking into a cohesive learning system.”
Waleed AlsarhaniFounder & CEO
“We wanted to create more than a marketplace. Distil Stack helped bring together supplier discovery, product listings, messaging, and real-time communication into one mobile experience. Their understanding of our business model was important in shaping the platform.”
Godfrey MsigwaFounder & CEO
“Managing relocation and visa applications requires coordination, visibility, and careful handling of information. Distil Stack helped translate these complex requirements into a structured platform connecting applicants, administrators, and office teams through a unified process.”
Michael RoeggeCompany representative
“Distil Stack helped bring structure to our digital coaching experience while keeping the client journey at the centre. Their ability to connect the technical requirements with the needs of a coaching business made the development process more purposeful.”
Hina KhanFounder & CEO
“Our vision required a learning platform that could combine education, engagement, and administration. Distil Stack brought these elements together through courses, quizzes, exercises, communities, and management tools designed around the learning experience.”
Gary John WallaceFounder & CEO
“Distil Stack understood the complexity of our coaching business and helped bring our vision into one connected platform. From programmes and communities to payments, automation, and client management, their engineering approach gave us a stronger foundation for delivering and scaling our services.”
Kim CalvertFounder & CEO
“Distil Stack understood the operational complexity of commercial laundry services and helped shape a platform around our business processes. Bringing customer accounts, credits, laundry status, and service management together created a more connected digital experience.”
Phil AkinFounder & CEO
“Distil Stack understood that a coaching platform needs to reflect the way a coach works with clients, not simply deliver content. Their approach helped translate our coaching experience into a structured digital environment that supports both our clients and our business.”
Maire NawazFounder & CEO
“Distil Stack understood that a fashion platform needs to make product discovery feel effortless. Their approach combined the technical requirements of digital commerce with an experience focused on helping customers explore and find products.”
Shauna CashellCompany representative
“What stood out about Distil Stack was their ability to understand the experience we wanted to create for our clients. They approached our coaching platform with attention to both the personal journey and the technology needed to support it.”
Danielle AmosFounder & CEORetrieval first in most cases. It's cheaper, easier to update and cites its sources. Fine-tuning helps when you need a specific style or format at scale.
Yes. We often take a model from a data science team and build the pipelines, APIs and monitoring that get it into production.
With task-specific evaluation sets, automated scoring and periodic human review. You see the scores on every release.
We agree a fixed scope and price after reviewing the work, system dependencies and acceptance criteria. The pricing guide explains approved ranges for the engagement types it covers. A written proposal confirms what is included before a build starts.
Agree the task, acceptable errors, business constraints and a non-AI baseline. Review data rights, labels and difficult cases, keeping evaluation examples separate from development data.
A comparison against a baseline using representative examples from the actual task. Retrieval, citations and refusal behaviour designed around the information users may access. Versioned evaluations show how a model or prompt change affects the cases that matter.
AI readiness
Ten questions, about three minutes. Find out what needs attention before you build.
08Related
AI Discovery & RoadmappingPinpoint the AI use cases worth funding and the order to build them in.
AI Agents & Workflow AutomationAgents and automations that move work between your systems, with people in the loop.
Data Engineering & MLOpsPipelines, warehouses and ML infrastructure that keep data and models fresh.RAG chatbot development servicesA chatbot that answers from your documents. Not from its imagination.AI integration servicesAdd AI to the software you already run. No rebuild required.Business process automation servicesThe work your team repeats every day, handled.
AI AgentsCustom agents that act inside your tools, with clear permissions and audit trails.
Machine Learning & GenAI
Predictive models and generative features built, tested and deployed like production software.
