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Anthropic

Connect Anthropic Claude to your Bolna voice agents for smart, natural conversations. Handles complex multi-turn dialogue with 200K token context windows.

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At a glance

How Anthropic fits in the stack

Best for

Reasoning, policy handling, tool use, and response generation.

Use this layer when

You want to tune quality, cost, latency, or function-calling behavior.

Connects to

Transcribed caller input upstream and voice or actions downstream.

Voice Stack

The LLM is the reasoning layer

The LLM is the reasoning layer

This provider decides how the agent interprets intent, selects next actions, calls tools, and formulates responses. It is the decision engine inside the voice stack.

TelephonyPhone Network
STTListener
LLMReasoning
TTSVoice
ToolsActions

This page focuses on where Anthropic fits in a production voice stack. For full setup steps, credentials, and API details, use the documentation link above.

Overview

Anthropic's Claude models provide advanced reasoning capabilities and industry-leading context windows for building sophisticated voice agents. With Bolna's Anthropic integration, you can leverage Claude Sonnet 4's 200K token context window to handle complex, multi-turn conversations with exceptional nuance and accuracy.

Claude excels at tasks that requires careful reasoning, following complex instructions, and maintaining context across long conversations, making it ideal for technical support, complex sales scenarios, and multi-step customer service workflows.

Features & Use Cases

Massive Context Windows (200K tokens)
Claude Sonnet 4 supports up to 200,000 tokens of context, equivalent to a 500 page book. Perfect for agents that need to reference extensive documentation, maintain long conversation history, or process complex customer accounts.

Advanced Reasoning
Claude excels at multi-step reasoning, following complex instructions, and understanding nuanced requests. Ideal for technical support, troubleshooting, and complex problem-solving scenarios.

High Accuracy
Claude Sonnet 4 demonstrates exceptional performance on complex reasoning benchmarks, making it suitable for scenarios where accuracy is critical.

Use Case: Technical Support
Build voice agents that can troubleshoot complex technical issues by maintaining full context of previous interactions, system states, and documentation references throughout extended support calls.

Use Case: Sales & Discovery
Handle multi-step sales conversations that require understanding customer needs, product knowledge, and business context across multiple touchpoints.

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Keep exploring the voice stack

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Large Language Models

The LLM is the brain of your voice agent. It understands what callers say and decides how to respond. Bolna lets you swap between models like GPT-4o, Claude, and DeepSeek without changing your agent configuration, so you can optimize for speed, cost, or reasoning depth.

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Telephony

Telephony providers connect your voice agents to the phone network so they can make and receive real calls. Bolna supports managed integrations with major carriers as well as bring-your-own-carrier via SIP trunking, giving you full control over call routing, number provisioning, and cost.

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Speech-to-Text

Speech-to-text converts what callers say into text that your LLM can process. Transcription accuracy and latency directly affect how natural a conversation feels. Bolna supports streaming STT providers optimized for telephony audio, including specialized models for Indian languages.

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Text-to-Speech

Text-to-speech turns your agent responses into spoken audio. Voice quality shapes how callers perceive your brand. Flat, robotic speech kills trust while natural, expressive voices build it. Bolna integrates with the fastest TTS providers so responses sound human and arrive without awkward pauses.

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Tools & Workflows

Tools let your voice agents take action during a call, not just talk. Book a calendar slot, look up an order in Shopify, push a lead into your CRM, or trigger a multi-step automation in Zapier. These integrations turn voice agents from answering machines into workflow engines.

See where Anthropic fits in your production workflow

Use the demo to walk through provider selection, stack tradeoffs, and the exact workflow you want Bolna to automate.