Agent approved source use karta hai
Clinic timing, services, location
Consultation request pehle staff review karega. Final slot clinic team confirm karegi.
Aapki team busy ho, phir bhi customer ko turant sensible jawab mile. She Said AI business ki FAQ, policy aur workflow se answer karta hai, missing details leta hai, aur WhatsApp, Gmail, Calendar ya Sheets action ko review ke liye ready karta hai.
Best start: ek city, ek use case, ek approved script. Live calls, WhatsApp, payment aur calendar actions provider setup ke baad hi on honge.
India pricing dekho“Kal evening appointment mil sakta hai?”
Services, timing, location, price range aur booking rule.
Name, phone, preferred time, reason aur follow-up permission.
Staff final slot confirm karega. Agent overpromise nahi karega.
Illustration only. No live call. No appointment booked.

“Call uthaya nahi, lead gaya.”
Isliye agent ka job simple rakho: customer ko polite jawab, right questions, clean summary, aur staff ke liye reviewed next step.
Actual local workspace ke screenshots aur generated explainer visuals ek saath. Synthetic data use hua hai, real customer data nahi.






Yeh page model call ya message send nahi karta. Yeh dikhata hai ki business owner ko flow kaise samajh aayega.
“Kal evening doctor ka slot mil sakta hai?”
Clinic timing, services, location
Consultation request pehle staff review karega. Final slot clinic team confirm karegi.
“Main preferred time, patient ka naam, phone aur concern note kar leta hoon. Team confirm karke call back karegi.”
Preferred time: kal evening. Final confirmation pending.
Agent request banata hai. Booking ka final promise staff karta hai.
“Dwarka mein 2BHK visit karna hai, budget 70 lakh ke andar hai.”
Area, budget range, visit rules
Lead tab useful hoti hai jab area, budget, property type, visit time aur buyer intent clear ho.
“Main area, budget, visit timing aur buying timeline collect kar leta hoon, phir team ko clean lead mil jayegi.”
Area, budget, intent aur callback time check karo.
Staff ko half-baked missed call nahi, kaam ki lead milti hai.
“Mera order kab deliver hoga?”
Delivery policy, return policy, escalation rule
Order status live system se verify hota hai. Policy answer approved content se diya jaata hai.
“Order ID share kar dijiye. Main support team ke liye request ready kar deta hoon.”
Order ID, issue type, policy source aur customer consent visible hai.
Agent guess nahi karta. Staff ya connected system status verify karta hai.
Workspace mein aap instructions, sources, language, workflow aur action approval set karte ho. Phir test conversation chala ke result inspect karte ho.
Setup guide padhoGeneric chatbot sabko sell nahi hota. Pehle un businesses ko target karo jahan ek missed call ka value high hai.
Calls miss hoti hain, patients repeat call karte hain, receptionist busy rehta hai.
Parents fees, batch timing, demo class aur callback ke liye baar baar puchte hain.
Buyer budget, location, visit time aur urgency clear nahi hoti to lead waste hoti hai.
Staff kaam kar raha hota hai, phone nahi uthta, customer next vendor ko call kar deta hai.
Order, return, COD, size, delivery aur payment questions support queue ko slow karte hain.
Customer ko answer chahiye. Owner ko lead, proof, cost control aur safe execution chahiye. Product dono sides ko clear rakhta hai.
Scripts, word breaks, pronunciation notes, escalation lines aur fallback phrases test karo before live launch. Voice provider pluggable hai, so best Hindi-capable STT/TTS choose ho sakta hai.
Call, WhatsApp, email aur internal follow-up alag tools mein toot-te nahi. Same workflow se answer, details, draft action aur review receipt dikhta hai.
Agent apni marzi se policy invent nahi karta. FAQ, PDF, notes, price list aur website content se matching source passage dikhata hai.
Gmail, WhatsApp, Calendar, Sheets ya support action direct fire nahi hota. Owner exact payload, recipient, consent aur purpose check karta hai.
OpenAI, xAI, Google, ElevenLabs, Kokoro, local GPU ya rented GPU ke adapters ke liye architecture ready hai. Business ek vendor mein lock nahi hota.
One use case, reviewed provider budget, no hidden static-site billing, and clear separation between platform fee and usage fee.
Saved transcripts, feedback, workflow versions, action receipts and audit records se owner dekh sakta hai kya improve karna hai.
AI disclosure, opt-in, opt-out, recording, suppression and provider setup ko launch checklist mein rakha gaya hai so careless automation na ho.
Architecture provider-agnostic rahegi: official APIs, OAuth, webhooks, action drafts, receipts, aur exportable workflow definitions.
Opt-in ke saath approved templates, inbound messages, follow-up drafts aur opt-out handling.
Availability check, tentative event draft, staff approval ke baad booking confirmation.
Customer support replies, sales follow-up, invoice query aur reviewed outbound email.
Lead log, callback sheet, order query queue aur simple business reporting.
n8n-style graph thinking: trigger, question, branch, RAG, action draft, human review.
FAQ, PDF, policy, price list, notes aur website content se source-grounded answer.
Live integrations ko enable karne se pehle provider account, scopes, consent wording, opt-out rule, idempotency aur receipt checks verify honge.
Yeh actual local workspace ki short recordings hain. Har chapter mein captions aur written steps hain. Data sample hai, customer ka real data nahi.
In recordings mein koi live call, model request, WhatsApp, email ya payment send nahi hua.
Give a sample agent one clear reception task.
Keep the greeting and boundaries explicit, then save.
Open the conversation workflow and inspect its connected steps.
Validate the graph, then publish an immutable version.
Run a local customer question without placing a call.
Read the saved transcript and identify one useful improvement.
Save feedback, then use it to guide the next revision.
A local repair request needs different questions from an online order enquiry. Choose a market to see a practical starting point.
Indian customers patience nahi rakhte. Agar call miss ho gayi, WhatsApp late gaya, ya staff ne half detail li, sale kisi aur ke paas chali jaati hai. Start with one simple agent: customer se service, area, budget hint aur callback time leke team ko clean summary de.
Built around: Founder, clinic/front-desk owner, coaching centre, real-estate desk, repair/service business, D2C support lead.
Try the exampleCustomer ne call ki, team busy thi. Agent service, locality, urgency aur callback time collect kare. Staff ko bas clear lead open karni hai.
Agent customer ki need samjhe, approved message draft kare, aur team send karne se pehle review kare. Consent aur opt-out visible rahe.
Customer preferred slot de. Agent bole team confirm karegi. Calendar booking ya payment tabhi ho jab setup verified ho.
India pilot ke liye pehle ek city, ek use case, approved Hinglish script, opt-in wording, escalation rule aur owner review rakho. Indian number, WhatsApp, payments aur commercial calling live karne se pehle provider approval and policy checks zaroori hain.
These are proposed pilot examples. Language quality, local numbers and live integrations must be verified for your setup.
Pehele ek repeatable request choose karo. Jab wo reliably kaam kare, tab channels aur countries expand karo.
She Said AI ek use case at a time launch karta hai. Provider behavior, Hindi voice quality aur production readiness live setup mein verify honge.
Founder
Magus Verma has built payment, pricing, and automation systems at Google, Amazon, and Media.net. He studied Computer Science and Engineering at IIIT Delhi.
B.Tech, Computer Science and Engineering, IIIT Delhi, 2012 to 2016
Past roles are listed for background. Employers do not endorse this product.
Explore plan se product samajh aata hai. Paid plans mein aapke business ka real workflow, approved script, knowledge setup, integrations review aur launch support milta hai.
Live calling, WhatsApp, Gmail, Calendar, Sheets, model usage, phone number, Razorpay fees aur taxes provider ke hisaab se separate quote mein lock honge. No surprise billing.
Workspace, workflow setup, reviewed action layer, product support and included improvements.
Calls, model, STT/TTS, WhatsApp, email, phone number and payment provider charges depend on your accounts.
One-time setup and applicable tax written quote mein confirm hoga before activation.
A one-time assisted setup starts at ₹5,999. Paid plan lene ka reason simple hai: free site product explain karti hai; paid launch mein aapke real business ke sources, scripts, workflow, integrations and review process configure hote hain.
Static website payment details collect nahi karti. Logged-in workspace hosted checkout open karega, subscription status verified webhooks se update hoga, aur paid access current payment proof se gate hoga.
Email/OTP login se workspace open karo. Team setup and role controls next production step mein expand honge.
Launch ya Guided plan select karo. Account ke andar hosted Razorpay checkout open hoga when live billing is configured.
Use case, language, greeting, boundaries, knowledge sources and escalation rule set karo.
WhatsApp Business, Gmail, Calendar, Sheets, voice provider and phone number setup status clear dekho.
Hindi/Hinglish recordings, simulations, consent checks and action approvals pass hone ke baad live route enable karo.
Razorpay live checkout, invoices, mandate rails and tax display require final merchant activation, plan IDs, webhook secret and sandbox acceptance before customer charging.
Kyuki India mein buyer impatient hota hai. Agar call miss hui ya WhatsApp late gaya, customer doosre seller ko ping kar deta hai. Product lead capture, answer consistency aur follow-up speed improve karta hai.
Haan, workflow Hindi, Hinglish aur English ke liye design ho sakta hai. Live voice quality chosen TTS/STT provider par depend karegi, isliye first rollout mein exact scripts aur recordings test honge.
Customer workflow mein action draft banega. Provider OAuth/API setup, consent, opt-out aur owner approval ke baad hi real send, booking ya sheet write enable hoga.
Nahi. Jab tak provider setup aur business approval complete nahi hota, agent request collect karega aur staff review ke liye next step ready karega.
Start one use case se hoga. Monthly platform fee, provider usage aur setup scope pehle written mein decide honge. Website khud paid call, model ya AWS resource start nahi karti.
Wahin se start karo. Information add karo, response define karo, next step test karo.