AI-native decision intelligence

From forecasts to decisions your business can execute.

UpSynQ connects demand signals, real-world constraints, forecasting, optimisation and scenario planning, so enterprises can decide what to produce, procure, allocate and change when conditions move.

Built for integrated business planning. Live in day-ahead power forecasting.

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A forecast-only plan versus a feasible recommended plan Chart of two operating levels. Five constraints — two operating limits, a minimum operating level, a supply or policy limit, and the requirement — enclose a region of feasible plans. A candidate plan that simply follows the forecast sits outside the region because it exceeds the supply limit. The recommended plan sits at the best feasible corner of the region. Operating level A → Operating level B → Operating limit A Operating limit B Supply / policy limit Requirement Minimum operating level Feasible plans Candidate plan over supply limit Recommended plan feasible · best trade-off
Illustrative A forecast suggests the requirement. A decision has to fit capacity, supply and policy — and be the best feasible plan.

  • Signed engagement

    Enterprise integrated business-planning engagement with a fast-growing Indian pharmaceutical manufacturer.

  • 96 blocks / day

    Day-ahead load forecasts for a power utility, at 96.8% average block-level accuracy across counted live days.

  • 8.3% WAPE

    Forecast error on a sealed three-month national × SKU pharmaceutical holdout.

A decision, worked through

Your systems record what happened. UpSynQ helps determine what should happen next.

Pick a disruption and watch the plan respond: signals in, constraints checked, alternatives priced, one recommended action — and a person who approves it.

Weekly supply plan Iced tea, 1 L · Plant North · Week 32
Illustrative example · synthetic data

Solutions

One platform. Different decisions. Shared intelligence.

A planning team needs its forecast to become a plan the plant can run. A utility needs it to become a power position it can afford, every fifteen minutes.

Integrated business planning

From the forecast to a plan the plant can run.

Most planning tools stop at the forecast. UpSynQ carries the number through every decision it touches: what the business agrees to sell, what each location needs, where supply comes from, and whether plants and materials can deliver it.

A better forecast is worth little if the plan it feeds is infeasible. The value sits in the hand-offs.

Explore integrated business planning
  1. DemandStatistical forecast at the grain you plan, with exceptions surfaced for review.
  2. ConsensusCommercial and supply teams review overrides; the agreed number is frozen with its rationale.
  3. Net requirementsStock, in-transit supply, expiry and minimum order quantities netted by location.
  4. Supply & procurementSource, transfer and purchase decisions against site rules and lead times.
  5. Production & materialsMaterial shortages, line capacity and batch feasibility checked before release.
  6. Decisions & approvalsA feasible plan, its trade-offs and a named approver.
Power & energy

The full cost of serving power, in one view.

A utility's decisions form one chain: what demand to serve, what to generate or buy, how to fuel it and what to do with the ash. Live day-ahead forecasting and shadow-tested bidding anchor it; the same architecture connects fuel, generation and ash, so each desk stops optimising in isolation.

Explore power & energy
  1. Demand96-block day-ahead forecast
  2. BidExchange bid packs within corridor rules
  3. Buy or generateOwn units, contracts or market
  4. FuelCoal source, quality and blend
  5. LogisticsRakes, sidings, stock cover
  6. AshOfftake, storage and dispatch
  • Live in daily operation
  • Built and shadow-tested
  • Connected solution scope

The same platform has also been applied, in technical studies, to constrained clinical staff scheduling.

Platform

The foundation underneath every decision.

Every business brings its own constraints and objectives. The foundation underneath is shared software — and it gets stronger with each deployment.

  1. 01Connect & prepare data

    Ingest ERP extracts and planning spreadsheets, map them to a common model, profile data quality.

  2. 02Forecast & evaluate

    Each series gets a model chosen by backtest; none ships that loses to a seasonal-naive baseline.

  3. 03Model constraints

    Capacities, lead times, order minimums, shelf life and policies as explicit, checkable rules.

  4. 04Optimise & simulate

    Search the feasible plans for each objective; test what changes when inputs move.

  5. 05Review & act

    Recommendations come with alternatives and trade-offs. People approve, adjust or send back.

  6. 06Measure outcomes

    Plan versus actual, overrides and exceptions feed the next cycle — and the next deployment.

Vertical rules specific to each business

PlanningBills of materials · shelf life · order minimums · site and sourcing rules · approval tiers
Power96 fifteen-minute blocks · bid corridors · unit ramp limits · coal quality · ash compliance

Shared foundation reused across engagements

  • Data ingestion & mapping
  • Data-quality profiling
  • Forecast model evaluation
  • Constraint modelling
  • Optimisation & simulation
  • Governed review workflow

Explore the platform

Where AI fits: language models help map, interpret and query messy enterprise data. Forecasts and plans come from statistical models and optimisation over explicit constraints.

Our work

Built against real operating constraints.

Work across pharmaceutical planning, power markets and consumer supply chains.

Read the full casebook

Pharmaceuticals

A three-level forecast, scored on a sealed quarter

National, depot and stockist forecasts reconciled so every depot plan adds up to the national number — rehearsed on history, frozen, then scored once on three months no model had seen.

Sealed-quarter error (WAPE) · national × SKU
8.3%

Found in the data: hundreds of depot-months showed zero sales while stockists kept buying — supply gaps, not missing demand. Repaired before any model learned from them.

Technical evaluation · separate from the signed planning engagement · Read the case

Power utility

Day-ahead load forecasting in daily operation

Ninety-six fifteen-minute blocks forecast and delivered every day. Alongside it, a constraint-aware bid engine builds exchange bid packs within the desk's rules in seconds, against roughly 45–60 minutes by hand.

Average block-level accuracy · across counted live days
96.8%

Built to connect: the same forecast is designed to drive schedule, buy-or-generate and fuel decisions — one utility model instead of separate desks.

Forecasting live · bid engine built and shadow-tested · Read the case

Retail distribution

Forty depots, thousands of sparse product codes

With a leading global supply-chain consulting firm: a four-month forecast for every product code at every depot — over 40,000 rows, most of them intermittent — scored on three rolling windows.

Accuracy · depot × product code, monthly / 4-month
71% / 79% vs 63% / 72% copying last year

Found in the data: the largest "discontinued" product had most likely been renumbered, with a sister code rising as it fell — one of 56 likely pairs.

Technical evaluation · accuracy = 1 − WMAPE · Read the case

Why now

A forecast is no longer the last mile.

Forecasting has improved fast. But a forecast is an input, not a plan. Turning it into one still means reconciling source data, encoding constraints that live in planners' heads, weighing trade-offs and getting sign-off — mostly across spreadsheets, calls and email.

ERPs record the transactions; dashboards report them. UpSynQ is built for the decision in between, and every deployment makes the next one faster to configure.

Built by a team with experience across enterprise product engineering, forecasting and optimisation — including Locus, Philips Research, 3SC, Razorthink and Disney — with doctoral expertise in operations research and advanced AI study.

Meet the thinking behind UpSynQ

Talk to UpSynQ

Show us the decision your team still makes in spreadsheets.

Bring one real planning or dispatch decision. We'll walk through it with its constraints, alternatives and trade-offs made explicit — and tell you plainly whether we can help.

Prefer email? hello@upsynq.com

We reply from hello@upsynq.com, usually within two business days.

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