Tabular Foundation Models
A new class of models learns strong priors for structured data and can deliver useful baselines without long training cycles.
Atlas is the proprietary prediction engine behind NeuraPay. It analyzes payment behaviour, communication patterns, and economic signals — and makes the optimal decision for every single case.
ERP data, invoices, and payment history are ingested in real time.
Macroeconomic signals and communication patterns are contextually enriched.
Atlas evaluates payment patterns, response latency, and channel affinity.
Channel, timing, tone, and escalation path are optimized per case.
Execution runs via NeuraAgent or workflow engine with full audit logs.
We track modern research in tabular foundation models (e.g., TabPFN) and translate the principles into claim decisioning: priors, calibration, and in-context signals.
A new class of models learns strong priors for structured data and can deliver useful baselines without long training cycles.
Decisions are contextual: history, responses, and macro signals — not just a static feature checklist.
Not just scores. Calibrated probabilities let finance teams set thresholds and policies with confidence.
Note: References to external research are for orientation. Atlas AI is NeuraPay’s proprietary decision engine.
Atlas classifies each case with calibrated probabilities rather than generic rules.
Atlas prioritizes the most effective contact path for each profile.
Timing is learned from outcomes and continuously refined.
Risk classes drive escalation paths and resource allocation.
Decisions execute inside guardrails with full traceability.
Atlas learns from real outcomes and improves continuously.
Select a profile and see how Atlas classifies channel, timing, tone, and risk.
Two decision systems with fundamentally different outcomes.
| Dimension | Static rules | Atlas AI |
|---|---|---|
| Decision logic | Fixed if/then trees | Transformer + RL, learning |
| Adaptability | Manual rule edits | Automatic from outcomes |
| Data sources | Internal master data | Behaviour + macro + communication |
| Decision time | Sequential / batch | < 50ms per claim |
| Explainability | Rule output only | SHAP feature importance |
| Accuracy | ~60-70% | 94% |
Atlas provides not just decisions, but evidence for why each decision was made.
From ingestion to action: every decision is part of an integrated flow.
Atlas powers decision intelligence across the platform — your team defines guardrails, Atlas optimizes within them.
In a live demo, we show decision intelligence with your business parameters.