AI that learns from every document you process.
Invofox continuously improves model accuracy through real-time feedback loops — ensuring your data extraction gets smarter, faster and more reliable over time.
Every learning cycle starts with structure.
Continuous improvement requires clarity. We start by defining schemas, building use-case datasets and setting measurable KPIs that track accuracy, coverage and latency.
Define exactly the fields and structure your pipeline expects.
Build a labeled dataset that becomes the source of truth for evaluation.
Track accuracy, coverage and latency against business-relevant thresholds.
The continuous improvement loop.
New documents trigger automated learning cycles. Users provide feedback on extractions via API or UI, the system measures performance against KPIs, and we tune the models in real time — without interrupting your workflow.
Continuous learning that drives real accuracy gains.
Real-time dashboards give you visibility into accuracy improvements, manual review reduction and processing speed — all measurable as documents are processed and feedback is incorporated.
Guided by people, perfected by AI.
Every human correction is validated against your KPIs and ground truth datasets, ensuring continuous improvement with enterprise-grade reliability.
Reviewers spot edge cases and refine the dataset directly from your workflow.
Each correction is benchmarked before it ever influences the model.
Every change is versioned and traceable for compliance and reporting.
Built for continuous improvement and total data protection.
Each customer's datasets and KPIs stay isolated and segmented per use case. All learning updates happen inside SOC 2, ISO 27001 and HIPAA-certified infrastructure.
Built to improve with every feedback loop.
Unlike platforms that rely on manual prompt tweaking or complex retraining, Invofox learns automatically and applies improvements immediately — creating compounding accuracy gains that accelerate, never plateau.