The Accountability Deficit
Citizen Agents Are Making Decisions. In a Democracy, That Demands Accountability.
India's government processes billions of citizen interactions annually. AI agents are being deployed for grievance management, document processing, scheme eligibility, and service delivery. In a democracy governed by the Right to Information Act, every agent decision must be explainable. The question isn't whether government will deploy agents — it's whether those agents will be accountable to the citizens they serve.
Our Approach
Agents Need Operations, Not Just Deployment Orders
Most government AI projects ship a model and declare a pilot success. Agentic systems — where AI reasons, decides, and acts on behalf of citizens autonomously — need a fundamentally different governance architecture rooted in democratic accountability.
Government Agents Without Operations
- Deploy citizen service agent, validate on test data
- No central registry of agents across departments
- Grievance routing agent reasons in a black box
- Scheme eligibility agent can't explain denials under RTI
- No fairness monitoring across demographics
- Compliance is a documentation exercise
Government Agents with Rotavision
- Every agent registered with sovereignty classification and deployment location
- Reasoning capture for every citizen-facing decision — RTI-ready
- Scheme eligibility agents with explainability in the citizen's language
- Human-in-the-loop for high-impact decisions — benefits denial, permit rejection
- Fairness monitoring across caste, gender, and regional demographics
- 100% sovereign deployment — GI Cloud, NIC, or air-gapped
Where It Matters
Agentic AI for India's Governance Reality
Not generic models — autonomous agents solving the specific problems Indian government agencies face when serving 1.4 billion citizens.
CPGRAMS received 7.6 crore grievances in FY24 alone — spanning every conceivable domain from pension delays to land disputes to ration card irregularities. These grievances must be classified by department, assessed for severity, routed to the appropriate authority, and tracked through resolution. Today, much of this is manual and slow. AI agents can dramatically improve speed and accuracy — but only if citizens can understand why their grievance was routed to a particular department, or why it was deprioritised.
In a multilingual democracy, grievances arrive in Hindi, Tamil, Bengali, Marathi, Telugu, and dozens of other languages. Agents must reason across languages, understand bureaucratic context, and route intelligently — not just pattern-match keywords. When a grievance sits unresolved for months, the agent's routing logic must be traceable. When citizens file RTI requests asking why their complaint was categorised a certain way, the system must have answers.
Orchestrate manages multi-agent grievance workflows across departments — classification, routing, escalation, and SLA tracking — with full reasoning capture at every step. Vishwas ensures every routing and prioritisation decision is explainable in the citizen's language, not buried in system logs.
India's government document ecosystem is staggeringly diverse. A single citizen interaction 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 caste certificate (format varies by state and decade), an income certificate, and land records that may be decades old. Over 2.5 crore passport applications alone flow through the system annually, each requiring document verification across this fragmented landscape.
Document processing agents need to extract, classify, verify, and cross-reference across this diversity — handling both digitally-issued e-documents and handwritten applications from rural tehsil offices. Each agent action — extraction, field mapping, identity verification, cross-referencing — must be captured with a complete decision trace. When an application is flagged or rejected, the citizen has a right to know exactly which document field failed verification and why.
Dastavez deploys document AI agents built for India's reality — multi-script OCR, handwriting recognition, format-agnostic extraction across decades of document templates — with every agent decision auditable. Orchestrate manages the document processing pipeline end-to-end, ensuring no application is lost between departments.
India has over 350 central and state government schemes — PM-KISAN, Ayushman Bharat, MGNREGA, PM Awas Yojana, scholarships, pensions, and hundreds more — each with its own eligibility criteria that overlap, contradict, and change frequently. A single farmer in Madhya Pradesh might qualify for six different schemes but know about only one. An urban migrant worker might be denied benefits because the eligibility agent couldn't reconcile address data across two state systems.
Scheme eligibility agents must reason across complex, interlocking criteria — income thresholds, caste categories, geographic location, family composition, land holding size, occupation, and more. When an agent determines that a citizen is ineligible for a benefit, the reasoning must be transparent and contestable. This isn't a UX nicety — it's a democratic right. In a country where scheme benefits can mean the difference between food security and hunger, opaque denials are unacceptable.
Vishwas ensures every eligibility determination is explainable in the citizen's language — not in bureaucratic codes or developer logs — with fairness monitoring across caste, gender, and regional demographics. Orchestrate coordinates multi-scheme matching agents with human-in-the-loop escalation for denials that affect vulnerable populations.
Solution Package
Sovereign Agent Governance Accelerator
A combined assessment, platform, and integration package for government agencies deploying citizen-facing AI agents — with RTI accountability, DPDP compliance, and sovereign deployment built in.
What's Included
Audit agent deployment across departments against RTI Act requirements, DPDP Act compliance, and GI Cloud security standards. Gap analysis with roadmap for citizen-facing agent accountability.
Orchestrate + AgentOps configured for government — grievance agents, document agents, and eligibility agents registered with sovereignty tiers, data classification, and deployment zones.
Pre-built connectors for CPGRAMS, DigiLocker, MyScheme, and e-Office platforms where citizen-facing agents operate. Governance alongside existing GovTech infrastructure.
Every agent decision captured with reasoning traces that satisfy RTI requests. When a citizen asks why their application was denied or grievance was routed, the system has audit-ready answers.
Real-time visibility into agent operations across departments — decision volumes, escalation rates, SLA compliance, and fairness metrics by constituency, district, and demographic.
Security & Sovereignty
Platform Stack
In a democracy, every AI agent that serves a citizen must answer to that citizen.
Sovereign AI isn't just about where data lives — it's about who governs the agents.
