Healthcare & Life Sciences
Streamlined hospital workflows and better outcomes for every patient.
ExploreAsk us what next quarter looks like.
Inventory, revenue, demand. We forecast it with above 90% accuracy, so your team acts before the shortfall happens.
Get your first prediction report
IN NUMBERS01
Our proof in numbers
20+
Years in industry
Twenty years of working with enterprise data across every shift from reporting to machine learning.
550+
Technology consultants
Data scientists, ML engineers, and statisticians who build, test, and refine predictive models with your team.
10+
Industries served
Industry experience that shapes every model, from demand planning in retail to risk scoring in finance.
07
Global offices
Teams across regions work in your time zone, keeping model reviews and updates on schedule.
What we do02
Predict what’s coming for you next month
What happens between the data you have and forecast your team can act on.
Forecast readiness assessment
Our team scores your historical data and current forecasting process, then lists the gaps. You learn what can be fixed now and what needs more time.
Revenue and demand forecasting
Models predict revenue, sales, and demand from your own historical data, so planning starts from a number.
Predictive maintenance
Models flag equipment that is likely to fail, using sensor and operations data most teams already collect but rarely look at closely.
Customer and churn prediction
Each customer gets a score for intent and churn risk, so retention budget goes to the accounts most worth saving.
Scenario and what-if planning
Models let you test a decision before you make it, so budget, staffing, and inventory calls have a number behind them.
Forecast monitoring and retraining
Markets change, and forecasts lose accuracy over time. Our team tracks forecasts against what happened to retrain and fix the gap.
Forecast readiness score in five minutes
Answer a few questions about your data, your planning process, and what you're trying to predict. You get a readiness score and the one forecast worth building first.
How we work03
How does a prediction project work?
Four stages take a rough idea to a live model, with a clear result at each one.
STEPS
Weeks 1 to 2
Baseline
The process starts with historical data and current process analysis to measure how accurate it is right now.
Weeks 2 to 4
Build the model
We build and test a forecasting model against your own historical data and real edge cases.
Week 4 to 8
Put it in front of your team
The prediction dashboard directly reaches the systems your operations and finance teams use.
Ongoing
Track and retrain
We track the forecast against what happened and retrain the model as demand, seasonality, or the market shifts.
Why sedin04
Why teams trust our numbers
Most forecasts stop at the model. These four things go further.
Predictive report with next steps
A biweekly report shows how the forecast compares with your target and actionable insights on fixing the gap.
Models that fit your industry
Our team has worked across industries, which makes them the best to learn about your seasons, customers, and constraints quickly.
Accuracy checked after launch
A forecast can be perfect on day one and off by month three. The team keeps checking results and tuning the model to hold accuracy.
The right person for each part
AI and ML engineers, software engineers, and statisticians share the work, from PhD-level researchers to early-career analysts, so each part goes to the person best suited to it.
Industries05
Industries we serve
Each project pairs up the model with industry knowledge, so the forecast highlights million-dollar opportunities hidden within your data.
Music
Manufacturing
Energy & Utilities
Retail & Ecommerce
Platforms and partners06
Platforms behind the forecast
Tools and platforms that support the process, Including PredictIQ, our own predictive maintenance accelerator.
FAQ07
Frequently asked questions
The accuracy of forecast depends on the data and how much history you have, but 80 to 90% accuracy is realistic for revenue, demand, and maintenance forecasting. We show you the expected accuracy before you commit to anything.
Usually less than people expect. Historical sales, transaction, or sensor data covering at least a year is enough for our team to start working. We assess what you have during the readiness check and tell you what's missing, if anything.
We monitor every model against actual outcomes and retrain it as patterns change. A forecast that isn't retrained goes stale quietly, which is why this is built into the engagement, not sold as an add-on later.
Yes. We deliver forecasts into the dashboards and tools your team already uses, Power BI most commonly, rather than asking you to adopt a new system just to see a number.
Get in touch08