AI Calling Implementation

Self-Hosted Voice Agents vs Vapi: Real Cost Analysis (TCO + Break-Even)

This post breaks down Vapi vs self-hosted voice agents using real TCO, not hype. It shows how per-minute fees hide platform tax, why costs spike after launch, and when self-hosting (Dograh, LiveKit, Pipecat, Vocode) wins on latency, control, and scale.

Voice AI Platforms Are Charging You for a Dashboard

The underlying voice stack (STT, TTS, LLM, telephony) is increasingly commodity. Closed platforms charge multiples of raw cost. The delta is UI, margin, and lock-in - not value. This post breaks down where the tax shows up: latency ceilings, debugging theater, roadmap distortion, and PII routing.

Building Voice Bot for Africa: Scaling Affordable Voice AI without Breaking

Voice AI is booming, but building for Africa, especially Nigeria, requires handling diverse accents, languages, and real-world conditions. In this webinar, Muyiwa Ogundiya shares practical lessons on scaling affordable, high-quality voice agents that work in African markets.

Voiceflow vs Open-Source Voice Agent: Which to Choose? Buy vs Build

Voiceflow vs open-source voice agents is a buy vs build choice. Voiceflow helps you launch fast with minimal setup, while open source is better for high call volume, compliance, data control, and long-term costs, speed today versus control at scale tomorrow.

How IIT Delhi Teamed up with Dograh for Alumni Day Invitations: AI Calling rollout

IIT Delhi partnered with Dograh to automate Alumni Day invitations across batches from 1966–2025. In one week, Dograh managed invites, captured RSVPs with family counts, answered FAQs, and gathered referrals. This guide shares the workflow, learnings, and recommendations for alumni associations.

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