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92
Houston, TX (USA) / Hyderabad (India) Late Stage / Pre-IPO

Autonomous Finance Platform for the CFO

HighRadius Corporation • Led by Sashi Narahari

🔒 Confidential
COI SCORE 92 VERIFIED

🔬 The Innovation Core

The Pain Point

AR and Treasury teams are bogged down by manual data reconciliation across disconnected ERPs and bank portals. Rule-based automation fails to handle unstructured data (e.g., email remittances, check stubs), leading to high Days Sales Outstanding (DSO) and trapped working capital.

The Solution

An 'Autonomous Finance' platform that moves beyond simple automation to AI-driven decision making. It uses proprietary 'Rivana' AI to predict invoice payment dates with >90% accuracy and 'FreedaGPT' to automate interactions (collections emails, dispute resolution) without human intervention.

⚡ Verified Impact

● Validated
10-20% (Avg)DSO Reduction
90% TouchlessCash App Automation
20%Bad Debt Reduction
3x Faster CollectionsProductivity
CERTIFICATION

Gold Standard

TRL 9/9

📊 Market Traction

Revenue History ($M)

Market Share

🧠 Analyst Verdict: Market Leader

"HighRadius has effectively defined the 'Autonomous Finance' category, differentiating itself from legacy AR vendors by proving that AI can predict *when* a customer will pay better than a human collector can. Their dominance in the Enterprise sector is secured by their massive data moat (trillions in transaction volume analyzed), though they face increasing pressure from ERP-native tools (SAP/Oracle) improving their own AI capabilities."

✅ Pros

  • Proprietary AI Stack: 'Rivana' (Predictive) and 'Freeda' (GenAI) are built specifically for finance use cases, outperforming generic LLM wrappers.
  • Outcome-Based: Sells on guaranteed KPI improvements (e.g., '10% DSO reduction') rather than just software features.
  • Network Effects: The 'HighRadius Network' allows suppliers to connect digitally with buyers, bypassing email entirely.

⚠️ Risks

  • Implementation Complexity: The platform's depth often requires significant professional services engagement, making it less viable for SMBs.
  • Cost: Premium enterprise pricing creates friction for mid-market companies compared to lighter tools like Quadient (YayPay).
  • UI/UX Density: The sheer volume of features and dashboards can present a steep learning curve for non-technical AR analysts.

🛠️ Use Cases

💡
Predictive Collections

AI prioritizes the call list based on who is *actually* at risk of defaulting, not just who is oldest.

💡
Cash Application

Auto-matching unstructured check remittances (scanned PDF) to open invoices with 95% accuracy.

💡
Deduction Management

AI validates shortage claims against shipping documents to auto-deny invalid chargebacks.

Market Maturity

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9

Commercial Grade

Fully audited operational history. Ready for scale.

6

Prototype / Pilot

Functional in relevant environments. High risk, high reward.

Current Maturity Status

TRL Score 9.0 / 9.0
  • check_circle Technology validated in lab (TRL 4)
  • check_circle System prototype demonstration (TRL 7)
  • check_circle Actual system proven in operations (TRL 9)
Transparency

Forensic Evidence Chain

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View Sample Audit Report →

Technical Diligence

> Architecture Review: PASS
> Security Audit: ISO 27001
> Scalability Test: 10k TPS

Customer Verification

> Client Interview: #8821
> Deployment Status: LIVE
> ROI Confirmed: 18% Savings

Certification Issued

STATUS: VERIFIED verified

Enterprise Action Center

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🛡️
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