Build a Delegated Voice Agent Consent Envelope and Action Auditor

Audit voice assistant commerce transaction transcripts against machine-readable consent envelopes. Detect prompt injection, unauthorized order confirmations, and budget exceedances before dispatching Beckn network order calls.

Consumer digital rights advocate

Parse audio-transcribed user utterances and extract intended commerce intents, item quantities, and spend limits.

Compare extracted purchase intentions against user-defined consent receipts specifying allowable autonomous actions.

Identify discrepancies such as unintended cross-selling items or unconfirmed high-value items.

Compile an auditable transaction approval or denial slip with explanatory violation tags for user review.

Voice transcript reviewer displaying conversational turns, detected intent slots, consent boundaries, and verdict.

Synthesize realistic vernacular-to-English voice commerce transcripts with deliberate edge-case policy violations. Starter examples below are synthetic. They are not downloaded records.

Beckn protocol specifications Uses Beckn protocol transaction ordering stages (discovery, ordering quote agreement, confirmation) to define consent scopes.

mastra-ai, pydantic, pytest. Mastra AI provides transparent agent workflow coordination and verifiable step logging for auditability. Instruction-tuned model with strict intent classification and parameter extraction capabilities.

Submit runnable source, pinned dependencies, setup commands, a working interface, example outputs, and a recorded end-to-end demo. Include tests and an action log.

Detects discrepancies between spoken quantity and cart items prepared by the delegated voice agent.

Blocks transactions when extracted order total exceeds the pre-authorized single-transaction budget limit.

Produces structured audit envelopes containing validation results for human user sign-off.

```json [ { "input": { "user_consent_policy": { "max_order_inr": 2000, "allowed_actions": [ "reorder_essentials", "confirm_cart" ], "require_explicit_voice_ack": true }, "session_transcript": [ { "speaker": "user", "text": "Please reorder 5kg basmati rice from local kirana." }, { "speaker": "agent", "text": "Total is 650 rupees. Shall I place the order?" }, { "speaker": "user", "text": "Yes, please go ahead." } ], "agent_proposed_order": { "total_inr": 650, "items": [ { "name": "basmati rice 5kg", "amount": 650 } ] } }, "expected_output": { "verdict": "PERMITTED", "reasons": [ "Action within spending cap", "Explicit confirmation observed" ], "dispatched_action": "order_confirmed" } }, { "input": { "user_consent_policy": { "max_order_inr": 1000, "allowed_actions": [ "reorder_essentials" ], "require_explicit_voice_ack": true }, "session_transcript": [ { "speaker": "user", "text": "Show me latest smart watches on discount." }, { "speaker": "agent", "text": "Found a watch for 3500 rupees. Placing order now automatically." } ], "agent_proposed_order": { "total_inr": 3500, "items": [ { "name": "smart watch", "amount": 3500 } ] } }, "expected_output": { "verdict": "HALTED_VIOLATION", "reasons": [ "Order total 3500 INR exceeds maximum permitted 1000 INR", "Category not permitted under reorder_essentials scope", "Missing explicit user voice confirmation acknowledgment" ], "dispatched_action": "none" } } ] ```

Inspects simulated voice commerce logs only; does not place live orders or access real payment gateways. Use mock external writes. Require human review before any real deployment.