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Platform

The engine, not a prompt

A VARTA call moves through seven explicit layers — L1 to L7 — each with a narrow, inspectable job. Call flows are deterministic step graphs: the same input takes the same path, every time. Only turns that genuinely need reasoning reach an LLM.

Design principles

Built for calls that have to be right

  • No invented prices, dates or IDs

    Logic, not the language model, owns anything that becomes a record. When AI runs, it chooses from a shortlist built by the workflow — never composes a number.

  • Answering without the pause

    Most turns are resolved by logic before a model is called, fillers play instantly, and audio already generated is replayed rather than resynthesised.

  • A cache that survives personalisation

    The stable skeleton of a sentence is cached once; only slot values (name, amount, order number) are generated. Context is part of the cache identity.

  • Every call has an itemised bill

    Every model call, synthesised character and second of silence is priced and attributed to the call — a real per-call ledger.

  • Every language your callers speak

    No English default inside the engine. Per-language content lives in the workflow, including gender-agreeing Hinglish grammar and mid-sentence code-switching.

  • Callers interrupt and backtrack

    Repeat-back, revisit-and-invalidate, and side-question-then-return are handled by deterministic handlers, not model reasoning.

  • Empathy your brand can govern

    Named empathy scenarios with explicit can / cannot / must-never policies — e.g. explain pricing and offer a callback, never invent a discount.

  • An AI co-author for the flow

    Describe the call in plain English; the co-author drafts steps, rules, FAQs and language variants — every change validated before it applies.

  • No vendor lock-in

    TTS, STT and LLM each sit behind their own provider abstraction, selectable per workflow. Switching vendors is configuration, not migration.

  • A regression gate, not a prayer

    An AI plays the customer across a scenario suite and diffs quality, per-layer latency and per-call cost before vs after every change.

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