Voice assistants, IVR systems, and natural language interfaces for enterprise.
Voice is a harder engineering problem than text and the gap is wider than most buyers expect. A text system that takes two seconds to answer feels responsive. A voice system that takes two seconds to answer feels broken, because human conversation runs on a rhythm that silence violates. Everything in a voice build is organised around that constraint: streaming recognition rather than waiting for a complete sentence, partial responses that begin before the full answer is computed, and a barge-in design that lets a caller interrupt the way they would interrupt a person.
Recognition quality is the other thing that separates the serious firms. Accents, background noise, speakerphones, hold music bleeding through, two people talking at once, and the specific vocabulary of your industry all degrade transcription, and a system tested in a quiet office by native speakers of the training accent will not survive a call centre queue. Ask what word error rate the firm measures, on what audio, and what the system does when confidence drops below a threshold.
The regulated uses need their own conversation early. Call recording consent, who is told that they are speaking to a machine and when, how a caller reaches a person on request, and what happens to the audio afterwards are legal questions in most jurisdictions rather than product preferences. A firm that treats disclosure as a configuration option has not deployed into a regulated environment, and the cost of discovering that after launch falls on you.
The agencies listed here work on phone systems, in-product voice interfaces, and multilingual deployments. Each listing names the services the firm works on and where it is based, plus an hourly rate where one has been published. Insist on hearing a recording of a real call from a live deployment, including one that went wrong, before you shortlist anyone.
What buyers ask most before hiring a Voice & Conversational AI partner, answered in plain terms.
A conversational AI agency builds voice and text dialogue systems — IVR replacements, voice assistants, speech-to-text pipelines, and multi-turn chatbots. They work with ASR platforms (Whisper, Google Speech-to-Text, AWS Transcribe) and TTS systems alongside LLMs to build end-to-end voice and text conversation experiences.
Conversational AI projects range from $15,000 for a focused text-based conversational agent to $150,000+ for enterprise voice systems with telephony integration. Mid-complexity conversational AI with multi-turn context and escalation handling runs $25,000–$75,000.
A text-based conversational AI system takes 4–10 weeks. Voice systems with ASR, TTS, and telephony integration take 8–20 weeks. Enterprise-grade voice platforms with multi-language support and compliance requirements take 4–9 months.
Conversational AI agencies work with ASR platforms (OpenAI Whisper, Google Speech, AWS Transcribe), TTS services (ElevenLabs, Amazon Polly, Google TTS), LLMs for natural language understanding, and telephony platforms (Twilio, Vonage) for voice channel integration. Dialog management is often handled with custom state machines or frameworks like Rasa.
A chatbot follows predefined scripts or decision trees — it can only respond to inputs it was explicitly programmed to handle. Conversational AI uses natural language processing and large language models to understand open-ended input and generate contextually appropriate responses. Conversational AI handles novel questions, maintains context across a conversation, and escalates gracefully when it cannot help.