Surface patterns, uncover root causes, and quantify impact. Then receive actionable recommendations that drive KPIs and revenue — automatically.
Live data streams exposing platform-wide trends and cross-channel distribution.
Watch the active footprint of our infrastructure. This dashboard continuously updates to show the growing number of verified companies deploying both Voice and WhatsApp AI.
Building trust through scale. This live counter displays the growing number of businesses globally that rely on our secure infrastructure to deploy and manage their AI agents.
Analyze the split between Voice and WhatsApp interactions. Understanding this channel distribution helps optimize routing budgets and capacity planning for your chat-first audiences.
Tracking real-time volume across Voice and WhatsApp AI agents. This proves our platform's ability to seamlessly manage dual-channel, high-volume customer interactions without dropping context.
Track real-time network load balancing. Our engine dynamically allocates compute resources between resolving inbound support tickets and driving outbound sales campaigns.
Live visualization of network traffic. Our routing engine dynamically allocates resources between inbound resolutions and outbound campaigns based on real-time load.
Track resolution rates, escalation patterns, and customer satisfaction with real-time data.
Weekly performance
Performance enhancement tools to continuously optimize your AI agent.
Clusters and categorizes call outcomes to identify systematic issues.
Generates ready-to-implement policy improvements from call patterns.
Quantifies business impact with projected revenue and retention gains.
Track satisfaction trends segmented by issue type and resolution method.
Predict call volumes by hour, day, and season to optimize staffing.
Get notified when anomalies spike — escalation surges, satisfaction drops.
CallSathi analyzes thousands of conversations in real-time, instantly extracting sentiment, intent, and actionable policy improvements.
Every interaction flows through our extraction pipeline, turning unstructured conversations into queryable business intelligence.
NLU & Extraction
Fetching company details from a database for every single message causes lag. We preload your static business rules directly into the AI's "KV-Cache Memory". The result? Zero-latency, instant, human-like conversations.
Customer asks: "What is your refund policy?"
Slow, repetitive database queries
AI searches an external database over the internet to find the refund policy.
Preloaded instant memory
Refund policy is already loaded in the AI's short-term memory. Instant recall!
Standard questions are answered instantly from memory (CAG). Complex queries automatically fall back to secure vector search (RAG).
Watch real customer questions stream through CallSathi's four-stage RAG guard. Every reply is either grounded in a cited document, or politely refused with a human handoff — there is no third option.
Answers shipped with citation
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Refused gracefully
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Hallucinated
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Rolling 24h · 0 answers analyzed · honesty 100.0%
Sanitiser
Prompt-injection patterns are neutralised before the LLM sees them.
Retrieval + Rerank
When the KB has nothing, we don't guess — we refuse and offer a human handoff.
Grounding check
Every claim in the draft answer is verified against the retrieved chunks.
Calculator tool
Numeric answers come from a deterministic tool, never the LLM.
Stream
Customer message · factual business
What an unguarded LLM might say
What CallSathi actually sends
Every shipped reply is cited. Every refusal is honest. There is no path through this pipeline that lets a fabricated number reach a customer.
Real-time platform totals
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Leads / day
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Bookings
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Follow-ups
Auto-categorization of intents
Watch how a real Instagram message becomes a closed lead in under 90 seconds.
Waiting for the first message…
WhatsApp will activate after the customer shares a phone…
Demo animation · ~14s