ISaaS Progress Log — Intelligent Survey-as-a-Service
v0.4 — Multilingual Voice Beta and Paradata Insights
- Added multilingual voice capture with auto-transcription for Indian languages; early tests show cleaner entity extraction and higher completion rates on voice-first journeys.[1]
- Introduced real-time paradata checks (timestamps, response latency, device markers) to flag potential fraud and interviewer effects during collection, not post-hoc.[1]
- Rolled out explainable validation messages so reviewers see “why flagged” and can override confidently.
v0.3 — WhatsApp Distribution + Dynamic Skip Logic
- Launched WhatsApp Business flow with dynamic skip logic and section-level progress save.
- Added instrument templates aligned to official survey structures, enabling rapid setup for modules like household roster and time-use blocks.[1]
- Improved accessibility with quick-reply chips and structured media prompts for proofs where needed.
v0.2 — Agentic Pipeline and Real-time Dashboards
- Stitched the agent workflow: Survey Design Agent → Distribution Agent → Validation Agent → Analytics Agent.
- Shipped real-time dashboards with instant indicators and drilldowns by geography, channel, and language.
- Added audit trails and data export with role-based access control for secure collaboration.
v0.1 — Foundation and Prototype
- Backend scaffold in Python (Flask/Django), frontend in React, and Firestore for scalable storage.
- Early survey design scaffolding: question types, skip logic, translations, and consent flows.
- Privacy-by-design baseline: encryption in transit/at rest, minimal data retention, and consent logging.
What’s shipping next
- Offline-first capture and delayed sync for low-connectivity regions.
- Enhanced standards library mapped to MoSPI manuals and UN household survey guidelines.
- Geo-enriched paradata and interviewer management features for large field ops.
- SDK for third-party question banks and analytics plugins.
Screenshot highlights (text-form)
- Dashboard: “Completion rate 78% | Voice 84% | WhatsApp 76% | Web 72%” with real-time flags panel.
- Designer: “Section: Expenditure → Auto-suggested probes; Language: Hindi/English; Skip: If Q3>0, show Q4–Q6.”
Code snippet (pseudocode)
# Paradata-informed validation
flag = any([
response_latency THRESHOLD,
device_fingerprint.duplicated(),
])
if flag:
queue_review(case_id, reasons=explanations)
Built with: CrewAI, Python (Flask/Django), React, Firestore, WhatsApp Business API, multilingual ASR/translation stack, encryption and RBAC.
Feedback is welcome—especially on voice flows and standards alignment for NSS/TUS-style modules.[2][1]
[1] interests.data_collection [2] projects.hackathon [3] https://ppl-ai-file-upload.s3.amazonaws.com/web/direct-files/attachments/84492374/4ee7c26b-9344-4ff8-b98a-8aec2f40e738/statathon-FINAL.pptx
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