AI and Data Intelligence That Works Inside Your Business
We find where AI genuinely fits your business, then build the machine learning, data engineering and automation to make it work.
AI Consulting · Machine Learning · Data Engineering · Workflow Automation · India · Ireland · USA
Applied AI Starts With How Your Business Works
AI is useful when it solves a real problem in your business. Sometimes you know exactly what's wrong. Sometimes you can feel the pain but can't quite see the fix. The answer might be machine learning, workflow automation, better data, an integration or simply a better process.
That's where we start. We look at how your business works today, where time slips away and what data you already have. Then we recommend what genuinely fits.
You're Probably Here Because
- You can see the inefficiency but not the technology to fix it
- Your data could be doing a lot more for you
- Your team loses too much time to manual work
- Key decisions still rest on individual experience
- You'd like to know where AI fits before you commit to anything
Business and Data Mapping
Prototype and Testing
Build and Integration
Launch and Optimisation
How We Put AI and Data to Work
Predictive Analytics and Machine Learning Development
We build machine learning models that learn from your own history and day-to-day data to help with decisions like demand forecasting, anomaly detection, risk scoring and resource planning. The model sits inside the application, dashboard or workflow your team already uses, so they see the answer right where they make the call.
Learns from real usage recommendations get sharper as more data comes in.
Works within your rulesyou stay in charge of limits and controls.
Keeps decisions visibleyour team can see what was recommended and why.
Data Engineering and Data Pipelines
Good AI starts with good data. Our data engineering services build the pipelines that pull information together from your databases, operational systems, APIs and spreadsheets, so your dashboards, models and automations all work from the same numbers.
Connected sourcesall your systems in one reliable view
Consistent dataevery report and model tells the same story
Built to growready for whatever you build next
Business Intelligence and Data Analytics
We turn your operational data into dashboards and reports built around the questions your team actually asks. With Power BI and Amazon QuickSight, you can track performance, spot trends and catch problems early. Nobody has to rebuild the same report by hand every month.
Live dashboards how things are going, at a glance
Trend trackingsee what's changing and why
Early alertsspot issues before they become problems
Generative AI and LLM Applications
We build generative AI and LLM applications that put your own knowledge to work. Think intelligent search, document processing, contextual Q&A, summarisation and knowledge assistants, all working from approved sources, with access controls that decide who sees what.
Your own knowledge answers built from documents you've approved
Secure by designpeople only see what they're allowed to
Faster answersless time digging through files
AI and Workflow Automation
Some of the biggest wins come from taking repetitive work off people's plates. We use workflow automation and AI, with tools like n8n and Zapier, to route information, handle approvals, process documents and cut out manual handoffs. Your team keeps working in the systems they already know.
Task routingwork lands with the right person automatically
Faster approvalsfewer delays and less chasing
Document handlingno more retyping the same details
Governed Domain Intelligence
Some parts of a business run on strict rules and their own language, like HR, compliance, operations, sales or client service. For these, we build governed AI systems that use your terminology, follow your policies and answer only from your documents, so every answer is accurate and traceable.
Approved sources onlyanswers come straight from your own policies
Clear boundariesit sticks to the job it was built for
Full traceability see where every answer came from
Map Operations, Build Systems , Run and Optimise
Bring us the problem. We'll work out the AI specification together.
We start by understanding how the work happens today. Then we find out whether AI, automation, better data, a software integration or a simpler change will make the biggest difference.
Map Operations
We sit with the people closest to the work and learn how the process really runs, exceptions and all. We look at where time goes, which decisions are hard, where the data comes from and where things get stuck.
From there, we separate the places where AI or automation will genuinely pay off from the ones where ordinary software or a process change would do the job better. You come away with a practical plan before any development begins.
Build Systems
Once the opportunity is clear, we build the data pipelines, models, automation, integrations and user experience around your workflow. It might sit inside an application you already have, connect several systems or become part of a new platform.
Where machine learning is involved, we test the model against past outcomes before anyone relies on it. Security, access permissions, governance and traceability are built in from day one.
Run and Optimise
Your business keeps changing. Your AI should keep up. We monitor performance, compare predictions with real outcomes, retrain models when needed and adjust rules as your operation evolves.
For automation and AI-assisted workflows, we also watch how people actually use each feature and whether it's saving the effort it was meant to. The goal is a system that keeps earning its place in your business.
Built for Production, Integration and Practical Use
We pick AI, data and automation technologies based on the problem, the systems they need to connect to, the data they handle and what they'll cost to run in production.
That might mean cloud AI, open-source models, on-device processing or straightforward automation. We choose whatever gives you the best balance of capability, privacy, performance and cost.
Machine LearningModels trained on relevant business data and validated against real outcomes
- Python
- PyTorch
- TensorFlow
- scikit-learn
Data and AnalyticsClean, accessible data and reporting for day-to-day and leadership decisions
- Python
- Pandas
- PostgreSQL
- Power BI
- Amazon QuickSight
Language Models and AgentsApplications that search, summarise and answer from your approved knowledge
- LangChain
- CrewAI
- Claude
Workflow AutomationConnected workflows that cut repetitive work and move information reliably between systems
- n8n
- Zapier
Data Storage and ServingScalable infrastructure for data pipelines, applications and machine learning workloads
- PostgreSQL
- Amazon S3
- Docker
- AWS
Member of Anthropic's Claude Partner NetworkOur Cloud Migration and DevOps team looks after infrastructure, deployment and model operations. Our Quality Engineering and Testing team keeps application and data quality on track.
Intelligence Built Into Everyday Operations
The Challenge
A US non-profit organisation runs a large internal application used by coordinators and field teams.
As the platform grew, we saw chances to make everyday work easier with AI, without asking anyone to learn a separate tool or change how the wider system worked.
The goal was to make existing tasks faster, simpler and more intuitive while meeting the organisation's operational and privacy requirements.
Privacy Built Into the Architecture
Sensitive user data is processed locally, on the user's own device. It's never sent to an external AI service. Existing access permissions and application controls stay exactly as they were.
So the experience improves while business data stays where it belongs.
Why the Architecture Matters
The useful question wasn't simply "Can AI do this?"
It was "What's the simplest, safest and most commercially sensible way to improve this task?"
We designed the solution to meet the operational need without adding a recurring AI usage bill.
What We Built
Less Friction in Everyday Work
We built intelligence into the existing platform that helps people reach the information and actions they're likely to need next, in fewer steps. It adapts to how the application is actually used, so the experience stays familiar.
A Simpler Way to Complete Complex Tasks
We also redesigned a high-effort task to feel more like a conversation. People share information naturally, the system handles the workflow behind it and the person still confirms the final action.
Results and Operating Benefits
In short: practical intelligence inside software people already use. Fewer steps, less manual effort, stronger data privacy and no ongoing AI usage cost.
Intelligence You Can Actually Use
Machine Learning Behind the Scenes
- Right food
- Right school
- Right amount
For a food service provider supplying schools, machine learning tackles a very different problem: working out how much food to prepare for each school and meal.
The system learns from recent sales and preparation patterns, supports preparation and ordering decisions and adapts as demand changes. The team can always see its recommendations. Business-defined controls stay firmly in place.
The payoff: less guesswork, better preparation and purchasing decisions, lower food wastage and fewer sell-outs.
Two very different kinds of intelligence, one principle. Understand the problem first, then use the simplest technology that solves it well.
Builder's Insight
View Our WorkThe hard part of applied AI is rarely choosing a model. It is understanding the work around it: the people, the data, the rules, the cost of running it and what a useful outcome actually looks like.
Collatzinc Engineering Team
View Our WorkIs This the Right Fit?
- You have a process, decision or workflow that could work better, but you're not sure what technology it needs
- You'd like to explore where AI could genuinely help before committing to development
- You have operational data that could support better decisions
- You want AI to work with your existing software, knowledge and workflows
- You care about privacy, control, running costs and adoption as much as the technology
- You want the team that builds it to keep improving it after launch
- Discovery that starts with your business problem, before any technology is chosen
- A straight answer on whether you need AI, automation, better data, a software integration or something else
- Data readiness and technical dependencies scoped before development starts
- Architecture choices based on capability, privacy, performance and cost
- Validation against real outcomes wherever it can be measured
- Ongoing monitoring and optimisation as your system and business evolve
- Only performance claims we've actually measured
related services
Custom ERP and Web App Development
AI built into the software your teams already use, including predictive dashboards, intelligent recommendations, automated decision steps and knowledge-assisted workflows.
IoT and Connected Systems
Computer vision, edge AI and analytics that turn sensor data into equipment monitoring, quality inspection and smarter connected operations.
Mobile App Development
On-device AI, smart recommendations and real-time analytics built into the mobile apps your teams and customers use every day.
eCommerce Solutions
Recommendation systems, demand forecasting, customer analytics and inventory intelligence across your storefront and the operations behind it.