Build a Delegated Voice-Commerce Action Safety Reviewer
Analyze voice assistant transaction execution traces against registered user consent policies. Detect prompt injection, unintended purchases, and voice authorization mismatches.
What you are building
The core problem, expected build, and operating context for this challenge.
Analyze voice assistant transaction execution traces against registered user consent policies. Detect prompt injection, unintended purchases, and voice authorization mismatches.
E-Commerce Consumer Safety Officer
Capture raw intent parse outputs from vernacular voice ordering sessions.
Reconcile requested cart actions against the user's active delegation and consent envelope.
Evaluate transcript for potential acoustic ambiguity or coerced command indicators.
Produce risk-scored transaction confirmation tickets requiring secondary tactile approval.
Safety operations queue showing flagged voice transactions, audio confidence scores, and consent scopes.
Generate synthetic voice order intent logs with varying levels of ambiguity and delegation scopes. Starter examples below are synthetic. They are not downloaded records.
Bhashini documentation Utilizes Bhashini ASR pipeline intent representations to assess vernacular speech transaction safety.
dspy, pydantic, fastapi. Optimizes verification prompts to assess command confidence and detect ambiguous speech intent. Local or hosted LLM with strong few-shot logical inference 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.
Identifies ambiguous voice commands where product variant or quantity is doubtful.
Cross-checks action parameters against delegated user permission boundaries.
Triggers step-up confirmation whenever confidence falls below established thresholds.
Emits structured safety audit receipts for each processed voice interaction.
```json [ { "input": { "session_id": "VCE-901", "asr_confidence": 0.94, "parsed_intent": "order_item", "item_name": "Basmati Rice 5kg", "consent_limit_inr": 1000, "order_value_inr": 650 }, "expected_output": { "action": "AUTO_APPROVE", "risk_score": 0.05, "requires_secondary_confirmation": false, "reason": "Clear intent, high confidence, within consent spend limits" } }, { "input": { "session_id": "VCE-902", "asr_confidence": 0.61, "parsed_intent": "order_item", "item_name": "Gold Coin 10g", "consent_limit_inr": 500, "order_value_inr": 65000 }, "expected_output": { "action": "HOLD_FOR_CONFIRMATION", "risk_score": 0.95, "requires_secondary_confirmation": true, "reason": "Low acoustic confidence and transaction exceeds consent limit by more than 100x" } } ] ```
Evaluates mock purchasing prompts; all financial transactions are simulated and non-binding. Use mock external writes. Require human review before any real deployment.
Participation guide
Evaluates mock purchasing prompts; all financial transactions are simulated and non-binding. Use mock external writes and human review.
How work is evaluated
Identifies ambiguous voice commands where product variant or quantity is doubtful. Cross-checks action parameters against delegated user permission boundaries. Triggers step-up confirmation whenever confidence falls below established thresholds. Emits structured safety audit receipts for each processed voice interaction.
Runnable source, pinned dependencies, setup commands, working interface, example outputs, recorded demo, tests, and action logs.
Challenge datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
Complete workflow
Capture raw intent parse outputs from vernacular voice ordering sessions. Reconcile requested cart actions against the user's active delegation and consent envelope. Evaluate transcript for potential acoustic ambiguity or coerced command indicators. Produce risk-scored transaction confirmation tickets requiring secondary tactile approval.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Correctness and evidence
Identifies ambiguous voice commands where product variant or quantity is doubtful. Cross-checks action parameters against delegated user permission boundaries. Triggers step-up confirmation whenever confidence falls below established thresholds. Emits structured safety audit receipts for each processed voice interaction.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Review interface
Safety operations queue showing flagged voice transactions, audio confidence scores, and consent scopes.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Safe execution
Evaluates mock purchasing prompts; all financial transactions are simulated and non-binding.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Capture raw intent parse outputs from vernacular voice ordering sessions.
Reconcile requested cart actions against the user's active delegation and consent envelope.
Evaluate transcript for potential acoustic ambiguity or coerced command indicators.
Produce risk-scored transaction confirmation tickets requiring secondary tactile approval.
Reference links and supporting material
Generate synthetic voice order intent logs with varying levels of ambiguity and delegation scopes. Supplied starter examples are synthetic, not source extracts.
Challenge setup
Configuration summary for this challenge.
Challenge input
Input details are not configured.
DSPy
Prompt and LM program optimization framework.
Evaluated output
No output checks are configured.
- Capture raw intent parse outputs from vernacular voice ordering sessions. Reconcile requested cart actions...
- Identifies ambiguous voice commands where product variant or quantity is doubtful. Cross-checks action para...
- Safety operations queue showing flagged voice transactions, audio confidence scores, and consent scopes.
- 2 public reference cases
- 3 configured tools
Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.
View technical recipe
Configured tools
- DSPy · Optional
- DSPy · Optional
- DSPy · Optional
Evaluation contract
- Complete workflow · Weight 40
- Correctness and evidence · Weight 30
- Review interface · Weight 20
- Safe execution · Weight 10
Reference cases
- 2 public reference cases
Workflow tasks
No workflow tasks are configured.
Recipe freeze marker
No recipe freeze time is recorded.