Traditional Forecasting Breaks Team Flow
Traditional forecasting slows execution: manual data toil, cold starts, fragile training cycles, and difficult integrations delay decisions, while regulatory and pattern shifts quickly break model reliability.
Still spending days cleaning data before forecasting can even start?
Teams are stuck in manual preparation, reconciliation, and feature setup. By the time a model is ready, the decision window has often passed.
Launching a new asset but forced to wait months for usable history?
New plants and assets start blind. Traditional approaches cannot produce reliable forecasts without long historical windows, delaying go-live and value capture.
Paying the training tax every cycle?
Training pipelines are compute-heavy, slow, and fragile. One failure can invalidate hours of work and force teams to restart from zero.
What happens when market rules change overnight?
Regulatory and structural shifts, like moving from 60-minute to 15-minute intervals, can make existing models instantly obsolete and trigger full redesigns.
Can your model survive drift, horizon changes, and new patterns?
Traditional forecasting breaks as frequencies, horizons, and behavior evolve, creating recurring rework, unstable outputs, and operational downtime.
Still facing integration nightmares before deployment?
Complex integrations with existing data and workflow stacks slow delivery, increase implementation risk, and delay business adoption.
Meet Credence
Credence is a Time Series Foundation Model (TSFM) trained on large, cross-domain datasets to deliver zero-shot, domain-adaptive forecasting. It is built for fast adoption through API and SDK integration, and natively supports modern agentic workflows via MCP.
Why you should choose us?
Instant Value
No waiting for data collection. No waiting for long training cycles. Plug-and-play forecasting that is ready from day one.
Built to Adapt
Continuously adaptive to changing data patterns and evolving business needs, ensuring remaining accurate over time.
Plug-and-Play
Deploy quickly with APIs and agentic pipelines. Connect to existing workflows with minimal effort.
Why you should trust us?
Real-World Applications
From energy and space to retail, mobility, and supply chain, Credence delivers continuous predictive intelligence for high-impact operational decisions.
Predict wind and solar generation with unprecedented accuracy by natively incorporating external co-variates like weather patterns, atmospheric conditions, and grid topology. Credence continuously learns from live data without retraining, delivering reliable forecasts for grid planning and trading.
In imbalance markets, reality constantly deviates from day-ahead schedules. Credence operates continuously, ingesting live weather and grid data to provide real-time forecasts so you can steer positions and avoid penalties before gate closure—zero training required.
Forecast satellite telemetry trends, mission resource consumption, and communication windows with continuous updates from live streams. Credence helps space operations teams anticipate anomalies and optimize mission planning.
Predict product demand by store, category, and time-of-day, integrating promotions, weather, and local events. Credence enables smarter replenishment and pricing decisions while reducing stockouts and overstock.
Forecast people flows in supermarkets, transport hubs, and city zones by combining sensor, calendar, and contextual signals. Credence supports staffing, safety, and service-level planning in dynamic urban environments.
Forecast inventory needs and replenishment timing across warehouses and distribution networks. Credence helps align stock levels with demand volatility to reduce carrying costs and service disruptions.
Meet the Team
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Ready to Start Forecasting?
Get in touch to explore how Credence can drive better decisions for your business.