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1분 만에 확인하기AI front desk for Aangan Studio: answers every call, qualifies on the founder's five rules, books on the call, hands off to designers (MESA Case 03)
저장소 README에서 가져옴
README 전체를 불러오는 중입니다. 아래는 저장된 발췌입니다.
An AI front desk for Aangan Studio, a 60-person interior design studio in Pune. It answers every inbound phone call, day or night, checks the caller against the founder's own five rules, books a consultation on the call, hands qualified leads to a designer with everything already asked, and shows the founder what the system costs and what it generates.
Status: built and deployed; not yet taking real calls. The voice agent, tools, gate, booking, handoff pipeline, follow-ups, dashboard and settings are live. Connecting a phone number and a pilot week come next (see Still open).README 전문 보기 ↗An AI front desk for Aangan Studio, a 60-person interior design studio in Pune. It answers every inbound phone call, day or night, checks the caller against the founder's own five rules, books a consultation on the call, hands qualified leads to a designer with everything already asked, and shows the founder what the system costs and what it generates.
Status: built and deployed; not yet taking real calls. The voice agent, tools, gate, booking, handoff pipeline, follow-ups, dashboard and settings are live. Connecting a phone number and a pilot week come next (see Still open).
Built for MESA Case 03 ("Nikhil: Unanswered Enquiries").
| Fact | Source |
|---|---|
| ~200 enquiries a month across phone, WhatsApp and a web form | Case brief |
| ~48% get no response within 48 hours | Case brief |
| ~33% arrive outside 10am to 7pm, when the 2-person front desk is gone | Case brief |
| Answered within 1 hour converts at 4x the rate of next-day | Case brief |
| Designers get forwarded messages with no context and re-ask everything | Case brief |
| Average project value ₹8 to 14 lakh | Case brief |
The founder's ask: "Every enquiry must get answered in five minutes, day or night. The ones worth my designers' time should reach them with everything already asked. And the system should be able to quote our standard per-square-foot pricing so people don't have to wait for that."
Quoting per-square-foot pricing is not built. The studio's own pricing guide says: "No number from this guide should be quoted to a client." The agent gives only the approved line ("Pricing depends on the site, the materials you choose, and the scope...") and offers to book. Price floors are used only inside a server-side budget check and are never spoken. There is no setting to turn quoting on.
| # | Tool | Job |
|---|---|---|
| 1 | Telephony | Now: Vaani direct-provisioned number. Later: Vobiz number over SIP. Swapping does not change the agent. |
| 2 | Vaani (vaanivoice.ai) | Live voice agent: talks, asks, calls our tools mid-call, books, transfers, calls back. One language per agent: English (en-IN). |
| 3 | Gemini API | After the call only: extract fields and write the handoff note. Does not re-decide the outcome. |
| 4 | Vercel (Next.js, region sin1) | Mid-call tool endpoints, webhook handlers, follow-up endpoint, dashboard. |
| 5 | Supabase (hosted) | System of record in its own aangan schema; pg_cron drives follow-ups. |
| 6 | Cal.com | Booking during the call (studio consult, site visit, principal-designer visit). |
| 7 | Telegram Bot API | Designer handoff with Accept, front-desk tasks, urgent alerts. Never contacts callers. |
| 8 | HubSpot | Contacts, deals and nurture tasks. |
| 9 | GitHub | Code, prompts and rules, versioned; pushes to main deploy to Vercel. Not part of the runtime. |
No SMS and no email.
Caller --> phone number --> Vaani live agent
| greeting: AI disclosure + recording consent
| lookup_caller(): history + today's date/time
|
+-- existing client / complaint --> urgent Telegram alert
+-- other (vendor, job, spam) --> front-desk task
+-- new enquiry
|
v
service fit + five criteria (plain code, called mid-call)
|
v
GATE (no score)
QUALIFIED / QUALIFIED_WITH_NOTES --> book on the call
NOT_QUALIFIED --> close gracefully
NEEDS_HUMAN --> transfer or callback
|
call ends --> webhook --> Supabase --> Gemini note
|
+-------------+--------------+
v v v
Telegram handoff HubSpot Founder dashboard
(Accept button) deal/task (cost + value)
pg_cron every few minutes --> follow-ups: unaccepted handoffs, overdue callbacks, nudges
From the founder's rubric: a lead reaches a designer only if it passes all five criteria.
| # | Criterion | Unclear? |
|---|---|---|
| C1 | Real project: design and execution, not advice | Ask one direct question |
| C2 | Site in Pune city or PCMC | Ask one direct question |
| C3 | Workable timeline | Ask one direct question |
| C4 | Budget not clearly too low (only if the caller volunteers one; never asked) | Pass, note it |
| C5 | Decision-maker on the call or authorised | Pass, note it |
Any clear fail closes the call gracefully. Asking about price never disqualifies.
| Setting | Default | Why |
|---|---|---|
| Designer accept: reminder / escalate | 15 / 30 min, office hours Mon to Fri 10:00 to 19:00 IST | Keeps the first designer contact inside the 1-hour window |
| Timeline hard fail | under 6 weeks | Services guide: "cannot begin... under 6 weeks" |
| Timeline flagged tight | 6 to 12 weeks | Design 3 to 4 weeks + execution 8+ weeks |
| Budget "clearly below" | under 50% of the price floor | Separates the rubric's own fail example from real leads |
| Commercial under 500 sq ft | send to a person, never auto-decline | Practised by the front desk but not written in the rules |
| Still unclear after one question | C1, C3: book with a note. C2: send to a person | "The designer establishes fit at the consultation" |
Every change is range-checked, needs a reason, and is kept in an audit log.
| Path | What |
|---|---|
src/lib/rules/ | The gate: parsers, office hours, wording, evaluateEnquiry (plain code, no model) |
src/lib/tools/, src/app/api/vaani/tools/ | Mid-call tools: lookup_caller, evaluate_enquiry, log_intent |
src/lib/booking/ | get_slots, book_slot, Cal.com webhook |
src/lib/pipeline/ | Vaani webhook events: link the call, safety flags, Gemini note, route by outcome |
src/lib/telegram/ | Staff messages and the Accept button |
src/lib/followups/, src/app/api/cron/followups/ | Reminders, escalations, callbacks, CRM sync, retention (every 2 min via pg_cron) |
src/lib/dashboard/, src/app/dashboard/ | Founder dashboard and admin settings |
src/evals/ | Eval runners, graders and the agent simulator |
prompts/ | Agent prompt and the note-writer prompt |
docs/ | Qualification rules, database, latency, privacy, agent prompt checklist |
Needs Node 22+, the Vercel CLI and access to the Supabase project.
git clone https://github.com/SathishAchilles/aangan-frontdesk && cd aangan-frontdesk
npm install
cp .env.example .env.local # fill in every value; see the comments in the file
npm run db:migrate # aangan schema
npm run db:migrate:test # aangan_test schema, rebuilt from scratch
npm run seed # settings, localities, festivals, placeholder staff (keeps admin edits)
npm run staff:add -- [email protected] "Your Name" admin
npm run dev
Production environment variables live in Vercel (vercel env). After changing one, redeploy with vercel deploy --prod.
| Command | What |
|---|---|
npm run lint, npm run typecheck | ESLint, and next typegen + tsc |
npm test | Unit tests (no network) |
npm run test:contract | Tool and webhook contracts against recorded fixtures |
npm run test:integration | Against the aangan_test schema |
npm run eval -- <name> | One eval; the report goes to evals/reports/ and aangan.eval_runs |
npm run setting:set -- <key> '<value>' "<reason>" | Change a setting with audit and version |
npm run staff:add -- <email> "<name>" <admin|viewer> | Create or link a dashboard login |
npm run telegram:setup | Register the Telegram webhook and commands |
Evals: gate-accuracy, tool-latency, tool-leakage, slot-compliance, agent-sim, note-accuracy, idempotency, week-simulation, data-integrity, metric-reconcile, replay-correctness, pii-scan. CI runs lint, typecheck, unit and contract tests on every push, and the evals that the changed files affect. Results show on the dashboard's Quality page.
Hard zeros, never allowed: a price figure spoken by the agent, a budget question asked, a lead marked qualified that fails a rule, a full phone number or secret in the logs.
vercel rollback (or promote the previous deployment in the Vercel dashboard).TELEGRAM_BOT_TOKEN; copy the HubSpot app token into HUBSPOT_PRIVATE_APP_TOKEN.