decision.ezee
Modernize Your Logic with 100% No-Code
Business Rules Management System.
Launch Products in Weeks.
A unified (BRMS) business rule management system that eliminates IT dependencies. Drag, drop, and deploy logic via an AI-driven business rules engine to launch loan products fast and error-free.
Built for Leaders
Who Own Speed, Risk, and Compliance.
Chief Operating Officers
Faster operations, fewer manual workarounds.
CIOs & CTOs
API-first, developer-friendly, no rule lock-in.
Chief Digital Officers
Modernize decisioning without core replacement.
Heads of Product
Ship rule changes without engineering delays.
10 Pillars of an Enterprise-Grade Decision Engine
AI Rule Authoring Studio
AI Scorecard Builder
Testing & Simulation
API-First Architecture
Maker-Checker Governance
Decision Flow Orchestration
Decision Tables & Grids
Incentive & Payout Engine
Data Sources Marketplace
Analytics & Monitoring
Static Rules Become a
Self-Learning Decision System.
AI Live Policy Execution
Millisecond rule execution through MCP.
AI Bidirectional Learning
Outcomes continuously improve recommendations.
AI Compliance & Audit Trail
Every invocation logged and traceable.
AI Context-Aware Decisioning
Live thresholds and eligibility at every decision.
AI Multi-Agent Consistency
One rule change syncs all decision agents.
AI Rule Recommendations
New rules and scoring weights from operational data.
Test Every Rule Before It Touches Production.
In-UI Simulation
Test rules and flows with instant field level outputs.
Bulk CSV/Excel Testing
Validate thousands of records across edge and limit cases.
Shadow & A/B Testing
Compare new rules with production before go live.
Automated Regression
Retest every version to catch issues early.
Six Reasons Enterprises Move Off Legacy BREs.
Zero-Code Platform
Business teams deploy rules
without code or IT reliance.
Real-Time Execution
Sub-100ms,
explainable decisions at scale.
Regulatory Agility
Deploy policy changes in minutes
and flag gaps before go-live.
Vendor Independence
Own your logic without
roadmap or licensing limits.
Enterprise Scalability
Multi-tenant execution
for high-volume lending.
Visual Workflow Maker
Drag-and-drop flows & Excel-compatible tables, no coding needed.
10 Ways Enterprises Deploy decision.ezee
Not just financial services. Any enterprise with decision logic that changes faster than IT can deploy it.
Credit & Risk
Loan Eligibility Rules
Filter by age, income, & score; auto-reject or route instantly.
Credit Scorecards
Score risk using bureau, banking, and behavioural signals.
Fraud Detection
Flag document, geo-IP, and velocity anomalies instantly.
Underwriting Flows
Orchestrate knockouts, scoring, verification, and decisions.
Compliance Checks
Enforce regulations and flag gaps before go-live.
Automation & Ops
Interest Rate Slabs
Risk-based pricing tables, Excel-compatible.
EMI & Serviceability
Configurable FOIR, DTI, and LTV logic.
Product Recommendation
Best-fit product matching by profile and eligibility.
Incentive & Payouts
Commission and DSA payout workflows.
Pre-Approved Offers
AI-led approvals based on behaviour & repayment history.
Which of These Is Your Team Still Doing Manually?
Enterprise Security & Compliance
Meeting the most stringent regulatory requirements while enabling innovation
ISO 27001:2022
SOC 2 Type II
AES-256
GDPR Ready
RBAC
SaaS
Cloud
On-Prem
Hybrid
Proven at scale across 4 continents
Trusted by 100+ Banks & NBFCs Across Segments
9/28 RRBs in India Run on ezee.ai
``` Legacy Collection Tools vs. decision.ezee
| CAPABILITY | LEGACY / TRADITIONAL BRE | |
|---|---|---|
| Domain Knowledge | Requires custom development | Built-in for BFSI + enterprise |
| Business Ownership | Developer-only | 100% no-code, business-controlled |
| Compliance & Governance | Add-on effort | Pre-integrated — maker-checker, audit trail |
| API Architecture | Backend only | Every rule = REST endpoint, JSON-native |
| AI Capabilities | None or separate product | Built-in — authoring, scoring, learning |
| Deployment Speed | Weeks to months | Minutes to hours |
| Testing & Simulation | Manual QA cycles | In-UI, bulk CSV, shadow, regression |
| Vendor Lock-In | Proprietary rule formats | Excel-compatible, export anytime |
The Full Credit Lifecycle. One Unified Ecosystem.
ORIGINATE
AI + No-Code LOS
Capture leads, run KYC, build journeys. 12 AI agents.
DECIDE
AI-Powered BRE
Author rules in minutes.
Sub-100ms. Audit-ready.
MANAGE
Servicing & Lifecycle
Real-time servicing.
Multi-product. NPA-ready.
RECOVER
Agentic AI Recovery
Predict, engage, resolve. Autonomously at scale.
Frequently Asked Questions
What is a business rules management system and how is it used in enterprise decisioning?
| Aspect | Hardcoded Rules | BRMS |
|---|---|---|
| Storage | Buried in app code | Central repository for non-technical updates |
| Updates for RBI changes | Requires code redeploys, risking delays | Live updates for faster TAT in loan approvals |
| Maintenance | Higher costs and errors | Reduced costs through separation |
How does a business rules management system differ from embedding rules directly in application code?
Unlike hardcoded rules buried in app code, a BRMS stores rules in a central repository that non-technical users can update without developers. Hardcoding demands code redeploys for RBI policy changes, risking delays; BRMS updates rules live for faster TAT in loan approvals. This separation cuts maintenance costs and errors.
What operational bottlenecks in financial services are typically addressed by a BRMS?
- BRMS tackles manual rule checks and IT dependency in high-volume decisions like credit scoring.
- It automates eligibility during online applications, reducing TAT from days to seconds.
- This curbs errors in collections workflows.
- Gartner notes up to 70% faster decision cycles in similar setups.
When should enterprises move from static rule execution to full decision orchestration?
Shift to full orchestration when rule volumes exceed 100 daily changes or compliance audits spike, as static execution falters under scale. In lending, this hits during peak disbursals needing real-time CIBIL pulls and risk adjustments. It delivers 15% CAGR in BRMS adoption for agility.
What criteria do enterprises use to evaluate business rules management platforms during vendor shortlisting?
Enterprises evaluate BRMS platforms when decision volumes, regulatory scrutiny, and rule complexity exceed manual control. Key criteria include rule governance, audit trails, API latency, and business user control; analysts report organizations prioritize platforms that support high STP without code dependency (Forrester).
How do risk and operations teams calculate ROI after deploying a business rules management system?
Teams measure ROI by avoided manual hours in underwriting and reduced compliance fines, tracking TAT drops and error rates pre/post-deploy. For instance, quantify savings from 5-second approvals versus hours manually. Risk ops weigh prevented losses against setup costs.
How are business rules governed, versioned, and audited across teams and environments?
Rules get governed via workflows tracking changes, who edited what, and approval logs across dev/staging/prod. Versioning uses visual diffs and comments for rollback; audits log every action for RBI reviews. This ensures traceability in loan rule updates.
What security, role-based access, and control requirements apply to BRMS in regulated industries?
BRMS demands role-based access, so operations views rules, but risk alone approves changes, plus encryption for CIBIL data. In BFSI, it enforces AML/KYC segregation and immutable audit trails. Compliance hinges on least-privilege controls.
How does a business rules management system integrate with loan origination, CRM, and data sources?
BRMS hooks via APIs to pull CRM borrower history, LOS application data, and credit bureaus for real-time scoring. During origination, it triggers rules on CKYC matches before disbursal. This unifies decisions without code rewrites.
How do organizations test performance and scalability of a BRMS under real-time decision loads?
Organisations simulate peak loads like 10,000 concurrent loan apps, monitoring response times under ramped users and data volumes. They define thresholds for throughput and CPU, using automation for passes. Continuous tests align with growth.
Is Your Decision Infrastructure Ready for Scale?
Each "yes" is a sign your current setup may be holding you back.
Select the statements that apply to your institution.
Your Next Business Rule Could Be Live Before End of Day
See decision.ezee with your own rules, your own data, your own
compliance requirements.
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