Frequently Asked Questions about Flowtaris AI Research

What is the accuracy of Flowtaris AI on unstructured invoices?
According to our 2024 Invoice Extraction Benchmark against 50,000 invoices across 15 formats and 8 languages, our GenAI document understanding engine achieves 99.2% accuracy, significantly outperforming legacy OCR (87.3%).
How does Flowtaris AI handle Conversational ERP queries?
We use a custom Natural Language to SQL (NL-to-SQL) engine specifically trained on finance schemas. It achieves 94% accuracy on simple queries and 82% on complex finance-specific joins, with a P95 latency of under 2 seconds.
What is Agentic Workflow Orchestration in Finance?
Agentic workflows utilize specialized multi-agent systems to handle end-to-end finance processes like AP automation. These agents handle planning, execution, verification, and self-correction, currently achieving a 78% autonomous success rate in research previews.
Research & Development

Innovation
Lab

Cutting-edge research on conversational ERP, GenAI document understanding, and predictive finance.

Active Research Tracks

Six tracks pushing the boundary of what's possible in enterprise finance AI.

TRACK_CONVERSATIONAL_ERP
Conversational ERP Interface
Beta

Conversational ERP Interface

Natural language → SQL → Action. Transform how users interact with ERP systems through chat.

NL-to-SQL 92% accuracy
Complex joins 67%
Latency <2s p95
RLS enforced at query layerRLS enforced at query layer
TRACK_GENAI_DOC-UNDERSTANDING
GenAI Document Understanding
Production

GenAI Document Understanding

Next-gen document intelligence: multi-modal, multi-language, layout-aware, context-rich extraction.

Accuracy 99.5%+
Formats 25+
Languages 15+
Layout understanding Yes
TRACK_PREDICTIVE_FINANCE
Predictive Finance Models
Pilot / Beta

Predictive Finance Models

Cash flow, revenue, expense forecasting with explainable AI. Ensemble models on ERP transaction graphs.

30-day accuracy 92%
90-day accuracy 87%
Features 200+
SHAP explainability Yes
TRACK_AI_GOVERNANCE
AI Governance & Compliance
Pilot / Beta

AI Governance & Compliance

Automated EU AI Act compliance, model monitoring, bias detection, and audit-ready documentation.

Risk classification Auto
Monitoring Real-time
Bias tests 12 dimensions
Audit trails Immutable
TRACK_AGENTIC_WORKFLOWS
Agentic Workflow Orchestration
Research

Agentic Workflow Orchestration

Multi-agent systems for end-to-end finance processes. Planning, execution, verification, and self-correction.

Agents 5 specialized
Success rate 78%
Self-correction 3 retries
Human-in-loop Configurable
TRACK_MULTIMODAL_FINANCE
Multimodal Finance Understanding
Research

Multimodal Finance Understanding

Vision + language models for financial documents: charts, tables, handwritten notes, stamps, signatures.

Chart extraction 89%
Table structure 94%
Handwriting 82%
Stamp/seal detection 91%

Open Benchmarks

Reproducible, transparent benchmarks for finance AI. Data, code, and methodology open-sourced.

Published2024-07

Invoice Extraction Benchmark

50,000 invoices across 15 formats, 8 languages. GenAI vs OCR vs Human baseline.

GenAI: 99.2%OCR: 87.3%Human: 99.8%
Published2024-11

AP Automation ROI Benchmark

237 production deployments. Processing time, cost/invoice, automation rate by platform/volume/industry.

Top quartile: 3 minMedian: 45 minCost range: $0.85-$8.75
In Progress2025-Q1

Text-to-SQL for Finance

Spider + custom finance schema. 1,200 NL questions → SQL. Executable accuracy + semantic correctness.

Simple: 94%Medium: 87%Complex: 67%Finance-specific: 82%
Planned2025-Q2

Exception Handling Benchmark

10,000 exception cases. AI-native vs Rule-based vs Human resolution time and accuracy.

AI-native: 2.3 minRules: 12 minHuman: 18 minAccuracy: 94% vs 78%

Stay at the Frontier

Monthly updates on new research, benchmark results, open-source releases, and lab experiments. No spam.

Read our Privacy Policy.