The company

Built by people who have had to make the plan work.

UpSynQ brings together enterprise product engineering, forecasting and optimisation to solve the decision that comes after the prediction. We have seen what happens when a good model meets inconsistent data, real capacity limits and a plan that people must actually approve and execute. We're building the software we wanted those teams to have.

See our work Explore the platform
Crossing the decision boundary On the left, signals arrive and run into limits. At a vertical line marked the decision boundary, one committed choice is made. On the right, the plan meets what actually happened, and the difference loops back to inform the next signals. SIGNALS CONSTRAINTS DECISION OUTCOME capacity supply policy decision boundary plan actual the difference informs the next plan
  1. Signals demand, prices, orders and events arrive — never perfectly
  2. Constraints capacity, supply and policy decide what is possible
  3. Decision one committed choice, made by someone accountable
  4. Outcome the plan meets what happened, and the difference informs the next one

Why UpSynQ exists

The forecast wasn't the hard part anymore.

Across enterprise operations, we kept seeing the same pattern. A reasonable forecast became a spreadsheet. Supply and capacity limits lived in other tools. The real trade-off was settled on a call, approved in an email — and by the next planning cycle, nobody could say why.

Better models didn't fix that. What was missing was software that carries the forecast through the constraints to a decision, and keeps the reasoning attached. That is what UpSynQ is for.

Before

  • Forecasta spreadsheet
  • Capacityanother tool
  • Trade-offa call
  • Approvalan email

One decision record

Inputs
the forecast and data it used
Constraints
what limited it, and which one bound
Alternatives
what else was possible, at what cost
Approver
who committed, and why
Outcome
what happened next

How we build

Three engineering convictions.

  1. 01

    Make the data decision-ready.

    Mappings, hierarchy reconciliation, structural breaks and quality checks are part of the product, not a project that happens before it. A decision is only as honest as the data underneath it.

  2. 02

    Let numerical methods do numerical work.

    Forecasts are chosen against baselines; plans come from optimisation over explicit constraints and tested in scenarios. Language models help where enterprise data is ambiguous — they don't do the arithmetic.

  3. 03

    Make the decision reviewable.

    Feasible alternatives, the constraint that binds, exceptions, approvals and plan versus actual matter as much as the forecast. A recommendation people can challenge is one they can trust.

The experience behind it

Enterprise experience. Deep mathematical foundations. Built for real operations.

UpSynQ brings together people who have built enterprise products, forecasting and optimisation systems, and the workflows that put their decisions into practice. Their experience spans routing, logistics, supply-chain planning, applied research and large-scale software delivery.

The team brings experience across Locus, Philips Research, 3SC, Razorthink and Disney, alongside experience helping build multi-million-dollar enterprise software businesses and serving large enterprises operating globally.

The technical team includes full-time PhDs specialising in operations research and people with advanced study in AI, with patents and research in related fields.

Enterprise product & engineering

Building and leading enterprise software for operational systems — logistics and routing, supply-chain planning and applied research.

Forecasting & optimisation

Statistical and machine-learning forecasting, operations research and mathematical optimisation — built on production-grade data engineering.

Getting decisions into use

Bringing decision workflows into real operations, and learning what that takes: data quality, adoption, reliability and the guardrails that make people trust the output.

Contexts the team has worked in Integrated business planning Power & energy Logistics Supply-chain planning

Why it compounds

Every deployment teaches the software something.

Industries differ in their objectives and rules. The work underneath them repeats — and each engagement leaves the platform better at it.

Stays with each customer

  • Their data
  • Their operating rules
  • Their objectives
  • Their approval process

The platform keeps

  • Mapping templates
  • Connectors
  • Model-evaluation patterns
  • Constraint abstractions
  • Execution and review workflow components

Each engagement refines software patterns. Customer data and operational rules stay specific to that engagement. See how the platform is built

Where the platform works today

Integrated business planning Connected demand, supply, production, procurement and inventory decisions. Explore Power & energy Demand, generation, procurement, fuel and logistics decisions in one position. Explore

Talk to UpSynQ

Bring us a decision your operation has to get right.

We'll look at it the way we look at every problem: the data first, then the constraints, then what a plan people can trust would take.

Talk to UpSynQ

Or email hello@upsynq.com

See our work