Conversational AI and Voice AI Development built for the conversations you are already having.

Conversational AI development builds software that processes or participates in spoken and written conversations. We build around a useful output or interface for calls, meetings and tickets.

That can include call intelligence, meeting intelligence, transcription, searchable knowledge or a scoped voice/chat agent. We define the workflow, its integration and the criteria for judging the result before selecting the models and processing path.

We quote against the scope: conversation volume, integration work, quality criteria and the data's legal and processing requirements. Our 30-day pilot has fixed scope and fixed price agreed before it starts; production work is quoted separately.

The billing model follows the engagement:

• Time and materials: billed hourly, quoted per project.
• Fixed price: outcome based, quoted per project.
• Team extension: billed monthly per team member.

Our conversation intelligence pilot runs for 30 days and delivers one structured output with an accuracy read on your own recordings. Scope and price are agreed before it starts.

We first settle sample access, processing and acceptance criteria. The pilot's duration applies to that defined output; a production integration or voice-interface build has its own scope and schedule.

Yes, we scope integrations that put the conversation output into your existing workflow, including CRM systems such as HubSpot. Feasibility depends on the available interfaces, access permissions and the fields or actions you need.

We map the recording source, destination, authentication and processing path with your system owners. They confirm access and field meaning; we build and test the selected connection. Platform restrictions or missing interfaces are identified during scoping.

Use a SaaS tool or platform-native AI when its outputs, integrations and data terms meet your needs. Enterprise products can support complex workflows and processing requirements, so assess the actual configuration rather than assuming custom development is necessary.

Commission a build when the required output, interface or integration remains outside that fit. Compare subscription and configuration costs with development and operation. A capable internal team can own either route if it has time for evaluation, integration and ongoing review.

We measure transcription quality on representative recordings from your workflow. The pilot's readout reports results against agreed criteria, including the accents, languages, crosstalk, line quality and domain vocabulary in scope.

We also test the result your team uses: extracted fields, summaries or an interface response can need different checks from transcription alone. Your reviewers help define correct examples. AI QA and evals provides the evaluation discipline; the readout identifies measured quality and its limits.

We agree sample access, processing locations, retention and permissions before pilot audio moves. The plan covers transcription and model processing separately, including provider paths, residency requirements and what happens to the sample after day 30.

unicrew is ISO 27001:2022 and ISO 9001:2015 certified, renewed through a multi-stage audit with Quay Audit UK. Our active security practice includes a dedicated security engineer and a part-time senior security consultant. We scope security review and controls for the work with your technical and data owners; provider terms and applicable legal requirements inform the design.

We select transcription, language processing, transport and infrastructure for the conversation task and data requirements.

Our owned-product experience includes Whisper, GPT models, AssemblyAI, WebRTC and AWS in Snaplore, which runs standalone or alongside Slack and Google Workspace. Talkmetry uses GPT models and AssemblyAI for HubSpot call intelligence. We draw on that listening and analysis experience when designing the processing path, with separate architecture and acceptance criteria for your voice/chat interface.

Compare partners on the conversation job they will deliver, the evidence for accepting it and the responsibilities for operating it.

• Ask how they test your recordings, languages and channels, and which output the quality measure describes.
• Review the processing locations, provider terms, retention, access controls and integration dependencies.
• Check what the cited work actually delivered, then agree implementation scope, handover materials and an operating owner.

Our pilot gives you an accuracy read on your own recordings. Our proof distinguishes owned conversation products from client search, streaming and QA engineering.

It fits when calls, meetings or tickets contain information your team needs in another workflow, or when a voice/chat interface has a defined job. You need a person who can approve the output and a practical route to the systems that will use it.

Compare native features, configured products and custom work against those needs. Commissioned development fits requirements that available configuration does not cover. If the main job is broader action planning across systems, AI agent development covers that orchestration.

Bring representative conversations you are authorized to share, a technical contact and a proposed output for the pilot.

• Samples: recordings that cover the audio, vocabulary and languages you want to test.
• Access: someone who can arrange secure sample handling and explain the recording source and destination systems.
• Acceptance: the output your team will use, such as a call summary, a reviewed compliance check or a CRM field, and the person who can judge it.