The Trust Deficit
Agents Are Making Decisions. Nobody's Watching.
India's financial sector isn't just deploying AI models — it's deploying AI agents. Autonomous systems that approve loans, flag fraud, verify identities, and process claims without human intervention. The RBI's own survey found that only 20.8% of regulated entities deploy AI — and of those, barely 12% use any form of explainability tooling. As these systems become agentic, the governance gap widens.
Our Approach
Agents Need Operations, Not Just Models
Most vendors ship a model and call it done. Agentic systems — where AI reasons, decides, and acts autonomously — need a fundamentally different governance architecture.
Agents Without Operations
- Deploy agent, validate accuracy on test set
- No central registry of agents or their autonomy levels
- Agent reasoning is a black box — no decision trace
- Compliance team reviews documentation post-hoc
- No policy enforcement at the agent layer
- Hope the agent doesn't hallucinate in production
Agents with Rotavision
- Every agent registered with identity, autonomy level, and risk classification
- Reasoning capture for every decision — full audit trail
- Policy enforcement at gateway, sidecar, and inline layers
- Human-in-the-loop controls with bounded autonomy
- Continuous fairness monitoring across Indian demographic categories
- Explainability in the borrower's language, not just the developer's logs
Where It Matters
Agentic AI for India's Financial Reality
Not generic models — autonomous agents solving the specific problems Indian financial institutions face every day.
480 million Indians have never had a formal credit product. Traditional credit scoring relies on CIBIL bureau data that simply doesn't exist for this population. Fintech NBFCs are stepping in — originating 76% of personal loans by volume — deploying autonomous underwriting agents that ingest alternative data, reason across multiple signals, and approve or deny loans without human review.
But who's governing these agents? When a crop loan agent in rural Maharashtra denies an application, its reasoning chain must be traceable. When an agent uses pin code as a proxy for caste, the system must catch it before it becomes policy. Bounded autonomy means the agent can decide within guardrails — but escalates when it encounters edge cases it wasn't built for.
Vishwas monitors every agent decision for fairness across Indian census categories, with explainability in 22 languages. Orchestrate manages the agent lifecycle — registration, policy enforcement, and reasoning capture — so institutions can extend credit to new populations without extending risk.
India's UPI processed 21.7 billion transactions in January 2026 alone — roughly 8,300 every second. Digital payment fraud surged over 400% to Rs 14.57 billion in FY24, with UPI fraud cases rising 85% year-on-year. A single fraud detection model can't reason across the complexity of SIM swap attacks, social engineering in regional languages, and mule account networks spanning multiple banks.
This is where multi-agent systems outperform monolithic models. Specialised agents — a transaction pattern agent, a device fingerprint agent, a beneficiary graph agent — each reason independently, then a coordinator agent synthesises their signals to make a decision. Every agent's reasoning chain is captured, every escalation is logged, and the entire multi-agent interaction is auditable.
Guardian monitors each agent for drift and reliability. Orchestrate manages agent composition, policy enforcement, and human-in-the-loop approvals — so fraud intelligence scales with UPI volume while maintaining full regulatory audit trails.
India has arguably the world's most complex identity document ecosystem. A single KYC verification might involve an Aadhaar card (Devanagari + English), a PAN card (English), a voter ID (in any of 12+ scripts), a ration card (state-issued, often handwritten), a driving licence (format varies by state and decade of issue), and utility bills from regional providers.
KYC agents need to extract, classify, verify, and cross-reference documents across this diversity autonomously — while rural NBFC branches still submit handwritten applications and urban lenders push e-Aadhaar XML through the same pipeline. Each agent action — extraction, masking, verification — is captured with a complete decision trace for compliance.
Dastavez deploys document AI agents built for this reality — multi-script OCR, handwriting recognition, Aadhaar masking for DPDP compliance — with every agent decision auditable against both RBI and DPDP Act requirements.
Regulatory Readiness
Mapped to the RBI FREE-AI Framework
In August 2025, the RBI released its FREE-AI framework — 7 guiding principles and 26 recommendations for responsible AI in financial services. Every regulated entity will need a board-approved AI policy aligned to these Sutras. Here's how Rotavision maps to each one.
Trust is the Foundation
Agents must be reliable and transparent. Every agent decision is captured with a full reasoning trace.
People First
Agents augment human judgement, not replace it. Bounded autonomy with human-in-the-loop escalation for high-stakes decisions.
Innovation over Restraint
Deploy new agents and capabilities without rigid restrictions — governed by policy, not by prohibition.
Fairness and Equity
Agent outcomes must be non-discriminatory. Continuous monitoring across Indian census demographic categories.
Accountability
The deploying entity is accountable regardless of agent autonomy. Full audit trail from agent registry to decision output.
Understandable by Design
Agent reasoning must be interpretable. Decision logic traceable by end-users and regulators, not just developers.
Safety, Resilience, and Sustainability
Agents must be secure and resilient to drift, adversarial inputs, and operational shocks in production.
Solution Package
FREE-AI Compliance Accelerator
A combined assessment, platform, and integration package that maps your agent governance maturity to the RBI's 7 Sutras — and builds the compliance layer before the regulator asks.
What's Included
Maturity audit across all 7 RBI sutras. Gap analysis mapping current agent governance to each sutra, with a board-ready roadmap.
Orchestrate + AgentOps configured for banking and NBFC workflows — agent registration with RBI risk classification, autonomy boundaries per sutra, and policy enforcement.
Pre-built connectors for lending origination systems, payment switches, and UPI infrastructure where credit, fraud, and KYC agents operate.
Board-ready AI governance reports aligned to FREE-AI disclosure requirements. Periodic sutra compliance snapshots for RBI submission.
DPDP-compliant consent capture at the agent level, plus borrower-facing explainability in vernacular languages.
Platform Stack
Deployment
480 million Indians are waiting for credit they can trust.
The question isn't whether agents will serve them — it's whether anyone is governing the agents.
Platform
