Services / AI Engineering
We build voice agents for calls and in-product conversations. Connected to your systems, designed for interruptions, and ready to hand over when a person is needed.
Defined tasks. Clear caller expectations. Measurable call outcomes.
The business case
A voice agent is not just a chatbot reading its answers aloud. Callers pause, interrupt, change details and expect a clear next step. We focus on workflows where conversation can reduce friction, with an outcome you can verify and an escape route when automation is the wrong fit.
Repeated enquiries, appointment coordination and structured intake with approved answers, accessible systems and a team available for exceptions. Baseline current call outcomes before deciding what to automate.
Complex negotiation, distress, consequential decisions or unclear identity. A secure form may also work better than voice for lengthy details. We do not equate fewer human transfers with better service.
Example engagements
These are illustrative scopes, not customer deployment claims. Feasibility depends on your telephony, systems, caller needs and operating policies.
Answer common questions from approved information, capture the reason for calling and route to the right team.
Escalate unsupported questions and requests for a person. Do not invent prices, policies or availability.
Measure: Resolution quality, routing accuracy and repeat contacts.
Find available slots, collect required details and confirm a booking through your scheduling system.
Read back dates and time zones. Confirm success only after the system accepts the booking; prevent duplicate writes.
Measure: Completed bookings, corrections and booking errors.
Capture an issue, perform approved basic triage and create a structured ticket with the caller's context.
Sensitive account information requires appropriate verification. Urgent or out-of-scope issues follow a defined escalation path.
Measure: Ticket completeness, handoff quality and time to triage.
Understand an inbound prospect's needs and pass a concise, reviewable summary to your sales team.
Use agreed questions and routing rules; avoid unsupported commitments or automated consequential eligibility decisions.
Measure: Useful qualified handoffs and information accuracy.
Support an approved outbound workflow such as appointment reminders or requested service updates.
Calling permission, local restrictions, time windows and opt-outs must be assessed before launch. Outbound calling is not automatically permitted.
Measure: Successful permitted contacts, opt-outs and complaints.
Add conversational voice to an existing application for guided support, navigation or bounded task completion.
Offer a text alternative and visible confirmation for consequential actions. Voice input is not proof of identity.
Measure: Task completion, accessibility and correction effort.
Real-time architecture
We assess both a modular speech-to-text → language model → text-to-speech pipeline and native speech-to-speech models. Modular stacks offer component-level control; real-time models can simplify the voice loop but still need explicit tool permissions, state and evaluation.
Handle the phone or browser connection, audio codecs, session lifecycle and routing. Establish how transfers, disconnects and keypad input work on your actual platform.
Recognise or interpret speech, detect completed turns and manage interruption. Account for end-of-utterance detection, network delay and audio quality instead of measuring model speed alone.
Use approved knowledge and bounded tools to progress the task. Keep business rules, identity checks and persistent records outside the model's conversational judgement.
Generate clear, concise speech and cancel buffered playback when interrupted. A correction must update state before the next action, not just alter the next sentence.
Connect to human support when required, with appropriate context. Trace agreed events, outcomes and failures while limiting sensitive audio and transcript retention.
A worked call journey
An illustrative inbound scheduling workflow shows where conversation helps and where application logic must take over. The same boundaries apply whether the agent uses a managed platform or a custom voice stack.
Identify the assistant, provide required notices and understand the service needed. Verify the caller where the requested records or actions require it.
Query the scheduling system for eligible slots. Ask for missing location or service details; never offer a slot inferred from general knowledge.
Read back the chosen date, time zone and relevant details. Accept corrections and write the booking only after the caller confirms through the agreed flow.
Announce confirmation only after a successful system response. If the result is uncertain, reconcile it or transfer with context rather than retrying blindly.
Test changed dates, interrupted confirmations, no available slots, slow lookups and dropped calls after a write. Confirm the final booking in the source system, not merely in the conversation summary.
Conversation engineering
A voice interface has to work in real time, with imperfect audio and people who change their minds. We design the conversation around the task, then test on the channels and conditions your callers actually use.
Detect when the caller has finished, handle pauses and let them interrupt. Cancel queued speech and keep conversation state consistent so the agent does not talk over a correction.
Read back critical dates, addresses and identifiers. Ask targeted clarification questions rather than repeatedly restarting the conversation; provide keypad input where appropriate.
Test required languages, accents, code-switching, noise and phone codecs. Support is validated per workflow; a provider's language list is not proof of quality for your callers.
Explain a slow lookup briefly, distinguish checking from completion and avoid filling silence with invented information. Set bounds for silence, call duration and repeated misunderstanding.
Systems & human handoffs
The agent should work with your CRM, scheduling tools, support desk and telephony platform. Those systems remain the source of truth; the voice layer cannot bypass their business rules.
Give the agent only the APIs and fields it needs. Validate arguments and permissions in code, use duplicate protection and verify successful writes before announcing completion.
Pass the reason for calling and relevant verified context to the receiving person through supported platform features. A transfer request is not complete until the connection succeeds.
Define queue, voicemail or callback behaviour, with caller permission where needed. Explain what happens next without promising a response time you cannot operationally support.
Handle failed lookups, disconnected calls and partial actions. Avoid blind retries that create duplicate bookings or tickets; reconcile uncertain outcomes before another attempt.
Safety, privacy & caller trust
Voice introduces obligations around disclosure, recording, personal data and outbound contact. Requirements vary by jurisdiction and use case. We work with your legal, security and operations teams; the implementation is not itself a compliance guarantee.
Plan clear AI disclosure and any required recording notice or consent. Define what happens when permission is declined, and provide a suitable alternative path.
Caller ID and voice similarity are not reliable authentication. Use an approved verification flow before revealing protected records or making sensitive changes; do not request passwords or one-time codes as conversational shortcuts.
Recording is not required for every workflow. Agree retention, redaction, access and deletion for audio, transcripts and tool traces, including provider storage and operational logs.
Treat speech and retrieved content as data, not authority. Test prompt injection, attempted data extraction and unauthorised action requests. Enforce permissions outside the model.
Review calling permission, do-not-call obligations, opt-outs and permitted calling times. Maintain suppression lists and stop instructions across campaigns rather than treating each call in isolation.
Keep medical, legal, financial and emergency decisions outside a general-purpose agent's remit. Agree specialist routing and urgent-call handling before launch; do not position the agent as an emergency service.
Evaluation & operations
We use scripted cases, authorised representative examples and live-channel testing. Audio, tool actions and handoff outcomes are evaluated together, with release criteria agreed for your workflow rather than a made-up universal success rate.
Check understanding, factual support, turn-taking, interruptions, repetition and recovery. Include noise, silence, corrections and frustrated callers; speech recognition accuracy alone is not task success.
Verify booking and ticket results, duplicate prevention, permission checks and successful transfers. Distinguish completed work from calls that merely ended without an error.
Measure response gaps and end-to-end task time on the actual channel. Test concurrency, network jitter, provider limits and slow tools; agree limits only after representative measurements.
Monitor failed calls, complaints, escalation patterns and cost within agreed privacy limits. Version prompts and models, review changes and maintain a kill switch with defined fallback routing.
Technology stack
These are options we can evaluate, not a compulsory bundle or a claim that every project uses them all. We check maturity, regional availability, licensing, data terms and your team's operating capacity before selecting tools.
Connect to phone networks, existing contact-centre infrastructure or browser audio. Number provisioning, regional availability, transfer support and call routing are checked during design.
Evaluate a custom real-time pipeline or managed orchestration. The choice depends on control, integration depth, hosting requirements, observability and recurring costs.
Consider separate speech recognition and synthesis or a speech-to-speech model. Benchmark voices, languages, interruption handling and data terms on representative calls.
Use approved knowledge and scoped tool interfaces. Model selection and retrieval quality are evaluated against your tasks; not every voice workflow needs a vector database.
Implement business rules, session state, validated actions, permissions and duplicate protection. Keep durable records separate from ephemeral audio sessions.
Combine conversation and tool traces with audio-specific testing. A text evaluation tool alone cannot assess telephony quality; deployment depends on transport and real-time runtime requirements.
Voice streaming has different runtime and networking requirements from a standard web application. Private deployment feasibility depends on every component, including telephony and speech providers; self-hosting one layer does not make the entire call private.
Economics & delivery
Compare cost per completed workflow with your current process. Include telephony, speech recognition and synthesis or real-time model usage, orchestration, infrastructure, storage and human follow-up. A lower cost per minute is not a win if callers have to call again.
Agree callers, tasks, approved answers, action boundaries and escalation routes. Assess consent, telephony access and operational readiness.
Output: A scoped call flow and measurable acceptance criteria.
Test the actual phone or browser channel, required languages and representative audio. Compare architecture and provider options.
Output: A feasibility assessment and initial evaluation cases.
Connect knowledge, validated actions and human handoff. Implement interruption, silence, refusal and failure states.
Output: A reviewable agent for the agreed call journey.
Exercise difficult calls, transfers, permissions and provider failures. Run a bounded pilot with an available human fallback.
Output: Release evidence, known limits and a rollout decision.
Document routing, deployment, evaluation, incident controls and responsibilities. Agree support and change review.
Output: Agreed source access, runbooks and an operating plan.
Start with a paid two-week sprint to assess the workflow and build an agreed first slice. Access, deliverables and review points are defined before starting. No long-term commitment is required; production rollout may need further work.
A call-process owner, approved information, authorised integration access and a team for handoffs. We also need contacts for telephony, security and legal review, plus agreed ownership of ongoing operations.
Related engineering
Explore the underlying agent development and practical design guidance for oversight and operational evidence.
Questions before you build
We can design for barge-in, including stopping generated audio and updating conversational state. Quality depends on the transport, speech stack and audio conditions. It needs testing on the actual channel, not just a browser demonstration.
We assess your telephony or contact-centre platform's supported transfer and context-passing features. We also define what happens when nobody answers or the transfer fails. Seamless transfer is not something to assume before checking the infrastructure.
We select and test providers for the languages and accents your callers use, including code-switching where required. Availability and quality vary. We do not promise a language or voice experience based only on a provider's advertised coverage.
Technically, outbound workflows may be feasible. Launch requires an assessment of calling permission, local restrictions, opt-outs, permitted times and provider policies. We do not frame automated cold calling as a default or universally permitted use case.
No. We agree whether recording is needed and what evidence is sufficient for support and evaluation. Audio and transcripts have separate notice, access and retention considerations, including copies held by providers.
Often, but it depends on routing, SIP support, provider availability and your current contracts. We assess the integration before proposing a change. Existing systems can stay the source of truth through scoped APIs.
Development scope and ongoing usage are assessed separately. Operating cost may include telephony, speech, model calls, orchestration, hosting, storage and human follow-up. We estimate cost per completed workflow, not just a headline per-minute rate.
A paid two-week sprint can assess one call journey and build the agreed first slice. Deliverables, access requirements and review points are set before starting; a complete production rollout may need further work. There is no required long-term commitment.
Start with the call
Tell us who calls, what they need and which systems or teams resolve the request. We'll assess feasibility, boundaries and a sensible first scope.