Enterprise voice AI for high-volume sales, collections and support calls
Arrowhead orchestrates 3-4 LLMs, routing each part of the conversation to the model best suited to it - optimising for the strengths of each, including Arrowhead's own in-house, self-hosted fine-tuned model.
Most voice AI still sounds like voice AI.
A single general-purpose model, prompted once and left to run, handles every part of a call the same way - the objection, the disclosure, the number read back to the customer. Quality drifts where it matters most, and customers notice within two turns.
The right model for each part of the call
Arrowhead orchestrates 3-4 LLMs, routing each part of the conversation to the model best suited to it - optimising for the strengths of each, including Arrowhead's own in-house, self-hosted fine-tuned model.
A model raised on conversations, not web text
Arrowhead builds and runs its own Small Language Model, trained on real conversational data rather than generic web text. It understands colloquial, everyday language the way customers actually speak - including mixed-language and informal phrasing - instead of sounding scripted or robotic.
Under one second at p90, measured
Measured end-to-end response was under one second at p90 across more than 100,000 datapoints from March to May 2026, covering Hinglish and other regional languages. Time to first token was 500 ms at p50, with the language model component under 300 ms. Conversations move without the pauses and dead air that give a bot away.
A voice that sounds like it's from here
Arrowhead develops its own Text-to-Speech engine, tuned for regional languages and accents. Accented voices can be matched to the local market you are calling into.
Real calls are messy. These hold up.
Customers interrupt. They switch languages mid-sentence. They pick up in a crowded market at six in the evening. A clean demo call proves nothing - the platform has to survive all of it.
One bot, 10+ languages, with switching inside a conversation
A single Arrowhead bot converses across languages, so one campaign can run across diverse regions without building a separate bot for each market. It handles 10+ languages, including English, with language switching within a conversation, where a caller moves between languages inside the same exchange.
Noise, interruptions and twenty-minute calls, handled
A layer of proprietary optimizations sits on top of the model. Noise cancellation keeps performance reliable in the noisiest environments. Filler-word and barge-in detection let the bot know when to cut in and when to hold back. Predictive caching pre-stores likely replies for near-instant answers. And a multi-agent system routes between three and four LLMs inside a single call, with automatic call analysis, hallucination detection and escalation to a human where a conversation needs one. A home-grown orchestrator holds the thread across natural, conversational interactions lasting 20+ minutes.
Deployed the way your compliance team needs it
Shared and quick to onboard, or fully isolated with every byte inside India. It is the same platform either way - what changes is where it runs and who else is on it.
Start shared, move isolated - your call
Arrowhead adapts to your privacy, compliance and scale requirements. Multi-tenant gives you shared, cost-efficient infrastructure and fast onboarding. Single-tenant puts you on a dedicated AWS account in a fully isolated environment, for the most privacy-focused customers.
Residency agreed per deployment, isolation where you need it
Shared or dedicated deployments are available. Residency is agreed for each deployment and recorded in the customer contract. Collections programmes for RBI-regulated lenders use India-only residency. Dedicated AWS isolation is available where a deployment calls for it.
Evidence you can review during procurement
Arrowhead's security evidence includes ISO 27001 and ISO 42001 certifications, a SOC 2 Type II report and an independent DPDPA assessment. Evidence scope and applicability can be reviewed during procurement.
Then it runs at your volume, inside your systems
The last mile is operational: who dials, what the bot can reach mid-call, and what you learn once the call ends. Arrowhead covers all three.
Telephony run end to end, or your dialer integrated
Arrowhead can manage telephony end to end or integrate the client's dialer. Elastic capacity is provisioned to the contracted throughput of each campaign. Calling identity is configured for the client and campaign type, with calling windows and retry limits set under applicable requirements.
Before, during and after every call
Arrowhead integrates with your existing systems through hooks at every stage of the call lifecycle. Pre-call hooks fetch data or run logic before dialling. In-call actions take real-time steps during the conversation. Post-call hooks trigger downstream workflows once the call ends.
See exactly where calls convert and where they break
Every call becomes actionable data. Built-in alerting flags call by call when a conversation breaks down, so issues surface on their own rather than waiting to be found, while detailed funnel analytics give a full, granular view of the overall conversion funnel.
Arrowhead AI is by far the #1 bot we have worked with - they competed against many other voice AI companies during our POC and we were highly impressed by the quality and output of the bot.
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