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Five dated research assets

AI voice research, pricing data and source-linked facts

Dvaarik Research is a collection of five free, dated resources for comparing AI voice products in India. The collection covers buyer pricing, white-label platforms, developer APIs, market statistics, and Dvaarik product facts. Vendor rows retain the native currency and billing unit shown by the source, identify what telephony or model costs are separate, and keep unavailable values as “Not published” instead of estimating them. Every asset shows its update date and links readers to the evidence used for that claim.

8

research datasets

109

dated rows and facts

9 Sept 2026

directory reviewed

Buyer comparisons

Compare finished platforms without flattening their prices

3 tools

Instagram comment-to-DM index

The five-step comment-to-DM mechanism, and tools serving India on free tier, paid price and channel scope — including where a single-channel tool beats us on price.

Web table

Developer research

Separate orchestration fees from the complete call cost

12 platforms

Voice AI API pricing index

Developer pricing compared by billing basis, included speech and model components, telephony, concurrency, open source and India support.

Web table, CSV and JSON

Evidence datasets

Reuse dated evidence without losing its scope

40 statistics

AI voice agent statistics in India

Dated statistics on voice AI, unanswered business calls, response time, mobile connections, languages and messaging, with named evidence.

Web dataset and source links

17 facts

Dvaarik AI facts

Short, scoped answers for Dvaarik pricing, billing, languages, channels and partner terms, each attached to a public source and checked date.

Web table, CSV and JSON

How the research is maintained

Vendor facts are read from current official pages and recorded with their native unit and check date. Missing public prices stay missing. Dvaarik facts are scoped to the relevant direct, partner, channel or developer product and link back to the current public source. Each child dataset states its own reuse licence; the directory does not assign one licence to every asset.