Custom ML models that score, classify, forecast and rank your own data, built to run in production. We build the product around the model, so your team ends up with a working tool: recommendations to act on, forecasts to plan against, alerts that fire early enough to matter.
Predictive AI reads the data your business already generates and makes a call about it: the forecasting, scoring, ranking and detecting behind everyday operational software. It's one part of our wider AI development services, and a different job from generative AI. Here's the line between them.
Reads the data you already have and hands back a number, a label or a ranking. It scores a record, classifies it, forecasts a value, ranks a list or flags the outliers. It measures and decides, and it's the side this page is about.
Creates new content instead: a paragraph, an image, a reply, a summary. A different kind of model and a different kind of product. It writes and draws, which is why it's a separate service.
Forecasting on your operational data
Models that turn a live data feed into a number your team can plan against. For LVLogics we built a web platform that ingests silo sensor telemetry and forecasts runout in real time, so operators know when a silo will empty and can schedule refills instead of guessing. Pulling reliable forecasts out of messy real-world sensor data took iterative processing and steady refinement of the calculation models, and that work is what makes them dependable enough to schedule against.
Optimisation and recommendation from live telemetry
Products that take a model's output and put it in front of the person who acts on it. The Roam AI ESP Platform turns an Electric Submersible Pump optimisation engine into a tool for oil and gas operations, and our part was the interface. We redesigned the platform and built its new front-end, turning complex operational data into workflows centred on a recommendations inbox and real-time well monitoring, with alerts, comments and historical setpoint data alongside. The optimisation model is Roam AI's. Our work was the front-end that makes its recommendations something an operator can read, weigh and act on.
Anomaly and threshold detection on time-series signals
Alerting that watches a stream of readings and flags what falls outside safe bounds while there's still time to respond. We built this into the LVLogics monitoring layer, and on the Roam ESP platform we built the front-end where operators manage alerts and monitor wells in real time.
Data-analytics and decision-support platforms
When the goal is to help a domain expert see and rank hundreds of metrics rather than automate the decision, we build the platform for it. We built a sports-analytics platform that maps hundreds of performance statistics onto 40-plus visualisation types (scatter, heatmaps, radar, strike-zone breakdowns, 3D pitch paths), so analysts can read the numbers at a glance and a decision-maker can act on them.
Fairness and bias evaluation of ML models
Stress-testing an existing model to check it behaves fairly across the groups it affects. We built Equality AI, a Webby-winning (2024) responsible-AI platform that helps data scientists evaluate and reduce bias in the clinical decision-making algorithms healthcare relies on.
Need a model trained from scratch on your data, full ML model development and an MLOps pipeline, or computer vision on images and video? Those are part of our broader custom machine learning development offering. Start there and we'll scope the right approach with you.
Demand forecasting software that estimates demand, load, risk or runout so teams can plan ahead instead of reacting.
Rank leads, tickets, accounts or records, or build churn prediction models that flag which customers are about to leave, so people spend time on what matters most.
Flag the transactions, readings or behaviour that don't look right, early enough to act.
Recommendation engine development that suggests the next product, article or action based on what a user has done before.
Sort incoming records (documents, requests, events) into the right category automatically.
Turn live sensor or telemetry data into a recommended setting or next best action.
01
Discovery
02
Scope and estimate
03
Build
04
Evaluation and launch
Discovery
We run workshops to pin down what you're trying to predict and what a good answer looks like, before a line of model code is written. Then we map and model the data the model will depend on, because AI quality starts with data quality. This is also where we agree the accuracy target that makes the model useful for your decision.
Scope and estimate
We prioritise with a must / should / could breakdown, and simulate the ongoing hosting and processing costs so scale holds no surprises later. You get a clear estimate and a billing model that fits (time-and-materials or fixed), and we build only once the scope and the data are confirmed.
Build
We shape your raw inputs (telemetry, records, time-series) into a form the model can use, benchmark the candidate approaches and pick the best performer while keeping it swappable. Around that we build what makes the output usable: the dashboards, the alerts, the recommendation flows and the human-review controls that turn a prediction into a decision your team can make.
Evaluation and launch
We measure the model against real benchmarks, tune it, harden the system, run final testing and ship to production, then support the go-live. For data that keeps changing, this is where we make sure the model holds up on the messy real-world edge cases, not only the clean ones.
Predictive models drive real decisions: who gets flagged, what gets scheduled, which setting a machine runs at. The guardrails matter as much as the accuracy.
Fairness you can check. A prediction that affects people should be measurable, so its impact can be tested rather than assumed. Equality AI is a whole platform dedicated to measuring and reducing bias in healthcare ML models, and that discipline informs how we approach any high-stakes prediction.
Human-in-the-loop where the stakes are high. Where a prediction carries weight, our default is that the model proposes and a person decides. On the Roam ESP platform we designed and built the front-end where that happens: a recommendations inbox where operators review what the client's model proposes and act on it.
Honest about uncertainty. We agree upfront that a model can't be guaranteed 100% right, set the accuracy bar that makes it useful, and design the product to handle the cases where it's unsure.
Python
AWS
Azure
Docker
Kubernetes
We specialise in premium mobile app development services, web development services, and everything that revolves around them: Product Design, Product Strategy, AI integration, QA and maintenance. Over the years, we've not only built powerful digital products but also played a key role in boosting conversion rates, optimizing performance, adapting to growing user bases, and improving app store rankings and reviews. These efforts have driven greater user engagement and significantly increased revenue.
From startups to scale-ups and industry giants—brands across various industries choose us as their trusted partners. They rely on us to transform their ideas into stunning products, deliver innovative solutions, and enhance existing projects to help them stand out in the market.
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Gab Test
Test
From the first day, Wolfpack was extremely committed, reliable and delivered solutions in outstanding quality. I also enjoyed that the Wolfpack team made lots of very useful suggestions and deeply cared about our company. Working with Wolfpack feels like working with your own team.
Axel Heinz
CEO and Founder of Makerist
They are informed, easy to work with, and communicative, bringing plenty of experience to the table. Overall, the quality of the work is brilliant. My business partner was skeptical about outsourcing it initially, but he ended up having his current applications rebuilt by Wolfpack too.
Raymond Valentine
CEO at FlexiDrive
The highly functional app has drawn enough users to make up 20% of the customer base across platforms. Wolfpack Digital is a communicative and reliable team that’s easily capable of integrating with the in-house development team. We communicated well. They responded to us rapidly, demonstrating their understanding of our business and any errors we might face.
Peter Kondrup
CTO at FirstAgenda
Wolfpack Digital delivered a functional backend despite the complicated nature of the app. Their work has received positive external feedback, and they've been commended for their ability to develop the product in a short timeframe. The team is supportive and understands the business goals.
Giampiero De Pasquale
CEO at Gloat
Working with Wolfpack Digital has been a blast. Gina and her team are very product-oriented and made sure they understood our needs before diving into building the app. This upfront effort paid off by meeting the deadline weeks ahead of schedule.
Flaviu Simihaian
CEO and Co-founder of Amplicare
The platform has been critical to business stability, and Wolfpack Digital was able to handle all technical issues. They were constantly available, either for an in-person conversation or a chat via technology (phone, email, Slack) and they refused to settle for sub-par or mediocre solutions.
Aurel Canciu
CTO at Elevatr
Consistently exceeding expectations, Wolfpack Digital has provided impressive deliverables on time to meet benchmarks. The team has been accessible and provided a detailed project overview to ensure a streamlined collaboration. They have supported a successful collaboration with a brand identity.
Krisztina Orosz
Chief Experience Officer, Anyline GmbH
Wolfpack Digital delivered functional mobile apps and played a significant role in the successful launch of the iOS app. In addition to having strong project management skills, the team is always accessible and honest. Their development work has been solid, making for a satisfactory experience.
Cristian Prodaniuc
Software Engineer at GoalPlay
They nicely replicated our brand elements into the design without much input from us. They had good ownership and delivery of the agreed tasks. Their help was essential in allowing us to focus on core back-end functionality with our in-house team. Wolfpack Digital was willing to adapt to our needs and learned the specific technologies we wanted to use on the project.
Tibor Barna
CTO at GoodBox
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Gab
QA
We were happy with Wolfpack Digital’s work, it's proven, very useful and we were able to manage projects from long distance. Thank you for your services!
Chen Lev
CEO at Storyball
Excellent group of professionals. Adrian and the team are very responsive; they understood very well our needs and went above and beyond to make sure the project was completed successfully. We look forward to continuing working with them!
Rafael Platas
Co-founder of Hyp3r
Wolfpack is the perfect partner for our organization: we can always rely on them to deliver high-quality code, transparent pricing, and exceptional customer service. Whether working on long-term projects or quick one-offs, Wolfpack always delivers.
Ben Sweeney
Director of Product Development at the Bosco
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Manual Testing vs. Automated Testing: An Intro to Effective QA!
Dragos
QA Specialist
Reading time: 6 min
Feb 18, 2022
As humankind constantly evolves, we explore and invent new ways to make our lives easier. Even if we are talking about something simple like washing machines or more complex things like self-driving cars (we can see a pattern here), humans like to automate.
Optimistic Frontend Development
Victor
Head of Web Development
Reading time: 6 min
Feb 15, 2022
With web and mobile apps, there is a lot of planning and designing. When you have a complex system, new features can break the app’s UX, performance, or code.
4 Important Healthcare Apps Tips for 2022
Dan
Head of Mobile Development
Reading time: 5 min
Feb 9, 2022
There's no need to say that the last two years have been very challenging from a medical point of view and there has been an increasing demand for healthcare apps. What are the aspects you need to pay attention to if you want to build a healthcare app in 2022?
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