AI implementation for businesses that need results, not experiments.

Challenge: KISNA needed to handle high volumes of customer queries across pre-order, post-order, and support — product availability, pricing, order tracking, returns, and complaint escalation — while keeping a premium brand experience. The support team was stretched thin, with no unified system for tickets, conversation history, or CRM integration.

What we built: We built KIA, an AI WhatsApp concierge for the full customer lifecycle — product discovery and recommendations, order tracking, returns, and complaint resolution. The bot auto-generates tickets, keeps conversation history, tags issues, and escalates to a human when needed, synced live with their CRM and helpdesk.

Result: Customers get instant answers on product info, order status, and support on WhatsApp, any time they message. Automated ticketing and logs give the team full visibility, and human handoff means complex issues are never dropped.

Challenge: An architectural brand wanted a digital extension of their in-store experience — a way for customers to discover furnishing, home accessories, and décor from multiple brands online. Product discovery, comparison, and purchase were split across websites, calls, and store visits.

What we built: We built a WhatsApp virtual concierge that takes customers from discovery and cross-brand comparison through to Razorpay checkout in a single chat. A dashboard lets the client manage brands, products, and services in real time, and the bot remembers context across conversations.

Result: Discovery, comparison, and purchase now happen end-to-end on WhatsApp. The client runs the catalogue from one dashboard, and customers get a personalised concierge that remembers preferences and past interactions.

Challenge: Hiranandani needed to reach a pool of around 35,000 homebuyer leads before the festive season, but did not have the manpower for high-volume outreach.

What we built: We deployed a multilingual AI calling agent fluent in English and Tamil — built to understand buyer intent, speak naturally, and continue the conversation on WhatsApp.

Result: In 2 days the agent called over 6,000 homebuyers and generated 195 qualified leads — fully automated, multilingual, and WhatsApp-supported.

Challenge: Complaint-resolution follow-ups were consuming call-centre bandwidth, keeping agents away from sales and new-customer acquisition.

What we built: We deployed an AI courtesy-calling agent that automatically checks complaint-resolution status with customers, without pulling human agents into every follow-up.

Result: The agent now handles about 1,867 calls per day, freeing 5+ human agents for revenue-generating work.

Challenge: iDAC needed to show up for complex, high-intent conversational queries on AI search engines — not traditional keywords alone.

What we built: We built a Generative Engine Optimization strategy so the brand ranks on ChatGPT, Gemini, and Perplexity for queries such as “best architecture exhibitions in Mumbai” and “top architecture awards.”

Result: 16% overall organic traffic growth, 38% targeted traffic increase from Mumbai, and 100% of referral traffic growth targets hit.

Challenge: Ordinary CCTV systems were collecting footage without turning it into usable intelligence for revenue, compliance, or cost control.

What we built: AVAA turns existing cameras into a live intelligence layer — spotting sales opportunities and customer flow, monitoring SOP and safety compliance, and flagging operational waste.

Result: Teams get real-time insight from infrastructure they already have: stronger revenue signals, automatic SOP checks, and lower operating cost.

Challenge: Leadership lacked a live view of retail performance, and dealer incentive settlement was a 15–20 day manual process. Sales and customer experience needed automation, not another static report.

What we built: We built a retail store performance dashboard for sales, footfall, scheme qualification, and store KPIs; a Virtual AI CEO that ingests business data and delivers executive recommendations; and a Dealer Incentive Engine that computes incentives from three uploaded files.

Result: Settlement moved from 15–20 days to real time. Leadership now sees every store live and gets always-on executive recommendations instead of a stack of reports.

Challenge: Dormant channel partners were hard to reactivate because engagement and performance data were not consolidated in real time.

What we built: We built a dashboard and backend that tracks every partner’s last interaction with the company and their manager, alongside dealer incentive earnings.

Result: Managers now have full context for personalised outreach — for example spotting a training gap and unused incentive, then reactivating a partner with tailored support instead of a generic sales call.

Challenge: Re-engaging dormant leads needed highly personalised communication, not generic cold calls.

What we built: We created virtual customer profiles that track past interactions and compare them against current projects, then used that intelligence to power personalised AI-driven calls.

Result: Dormant prospects are reactivated with specific context — for example a buyer inactive for 18 months who wanted a 3 BHK near a good international school was called about a new project launching next to a Global High School campus.

Challenge: The firm ran audit engagements across 5+ disconnected tools — spreadsheets, email, and shared drives — with no real-time visibility. Monthly WIP reconciliation took 3–5 days, invoices were fully manual, and payment health was judged on gut feel.

What we built: We built a unified AI practice-management dashboard covering engagements, PBC tracking, WIP and billing, time entry, and a client portal — plus a Payment Health Scoring Engine (0–100), ClaraGPT document analysis, and auto-generated invoice PDFs.

Result: WIP reconciliation went from 3–5 days to real time. Invoice generation dropped from 30 minutes to under 30 seconds. Five tools became one platform with role-based access and a self-service client portal with Stripe payments.

Challenge: Kisna’s sales and support team managed gold-order fulfilment across 25+ vendors with zero real-time visibility. Status tracking was manual — vendors were called every 7 days — so stores could not tell if an order was delayed, in finishing, or ready to dispatch. That created 21-day backlogs and task mismatches across 2,000+ orders.

What we built: We built a live Sales & Support Dashboard for the full gold-order lifecycle: store order receipt, credit-health checks, vendor assignment, QC, payment confirmation, and dispatch. It includes WhatsApp and email alerts via Kisna’s own number, a vendor portal, a QC Review Bureau with digital checklists, and a 7-day payment reminder engine, with role-based access.

Result: 2,124 orders across 28 states and 124 customers are now tracked live. INR 17.3 Cr in order value sits on one dashboard. 25+ vendors are moving onto a unified portal, and five disconnected workflows — assignment, vendor coordination, QC, payment, and dispatch — now run as one system.

Challenge: Quality checks on patient calls were extremely time-intensive for supervisors, creating bottlenecks in healthcare service delivery.

What we built: We built a custom AI quality-check agent that listens to calls and scores each interaction consistently out of 10.

Result: Evaluations are now consistent and objective, supervisor workload dropped sharply, and patient-care standards improved.

Challenge: Manual reconciliation between ERP and Tally data was slow and error-prone, with weak visibility into why figures did not match.

What we built: Our AI system reconciles ERP and Tally records using unique identifiers, flags discrepancies instantly, and calculates Net Balance, Permanent Difference, and Value of Receipts. A dashboard shows where differences exist and why.

Result: Reconciliation is faster and more accurate, audit visibility is stronger, and mismatches can be resolved without hunting through spreadsheets.

Challenge: The event needed attendance confirmed at massive scale, visitors guided to the right booths, and analytics captured throughout — without stretching human teams.

What we built: An AI calling agent confirmed attendance, an AI WhatsApp agent guided every visitor to their destination booth, and real-time analytics ran continuously during the event.

Result: 43,000 calls in one day, 100% navigation support, and 24/7 event analytics — with record turnout and a complete post-event dataset for the next edition.