Voice AI

Sub-second latency conversational voice agents (ElevenLabs, Deepgram, Twilio) for 24/7 inbound qualifying and appointments.

Core Capabilities & Engineering Deliverables

• Ultra-Low Latency Voice Pipeline (Deepgram + ElevenLabs + OpenAI Realtime)
• Twilio & SIP Telephony Phone Number Provisioning & Integration
• Live Cal.com / Google Calendar Real-Time Appointment Booking
• Natural Speech Interruption & Filler-Word Conversational Fluency
• Automated Post-Call Summaries, Sentiment Scores & CRM Updates

How to Evaluate Voice AI

Voice AI should solve a specific phone workflow such as triage, qualification, scheduling, or status updates, with clear escalation paths for people. We design the conversation, integrations, privacy considerations, and monitoring around the caller experience.

Start with the operating decision

A useful Voice AI engagement begins with the decision the organization needs to improve, rather than a preselected tool or deliverable. That means identifying the people affected, the current handoffs, the information they rely on, and the consequences of getting the work wrong. This gives the team a practical basis for deciding what should be designed, configured, integrated, or left out of the first release.

Questions that shape the scope

• Limit the first workflow to well-understood intents.
• Design a clear route to a human when needed.
• Test accents, noise, errors, and consent language.

For Voice AI, these questions prevent a proposal from becoming a list of fashionable features. They help separate a near-term release from later work, establish who can approve tradeoffs, and surface dependencies such as source data, third-party systems, brand review, legal review, or customer support.

A delivery plan people can operate

The strongest outcome is not simply a completed asset or deployment. It is a working process that the client can understand and maintain. For Voice AI, that normally means documented assumptions, named owners, review points, access boundaries, and an agreed method for handling changes. The delivery approach should make it clear what is being tested, what evidence will be reviewed, and what happens when the real-world workflow differs from the initial brief.

How to assess fit before committing

Before selecting a Voice AI partner, ask for the proposed discovery method, the information needed from your team, the choices that will be made together, and the limitations that could affect delivery. A credible plan should distinguish confirmed facts from assumptions. It should also explain how feedback will be incorporated, how sensitive information will be handled, and which decisions remain with your organization.

What to bring to discovery

A productive Voice AI discovery session does not require a finished specification. It does require access to the people who understand the work, examples of the current process, existing assets or systems, and clarity about the decision that will mark the project as useful. Bringing examples of edge cases and known frustrations is especially valuable because they expose the constraints that a high-level brief often misses.

Making progress visible

For Voice AI, progress should be visible through concrete artifacts: a clarified workflow, a reviewed design or plan, an implemented component, a test result, or an approved release decision. Regular review is not ceremony. It creates a place to challenge assumptions while a change is still affordable, and it gives the client a record of what has been agreed as the work evolves.

After the initial release

The first Voice AI release should create evidence for the next decision. Teams can use feedback, operational data, support questions, and adoption patterns to decide whether to refine the current scope, connect an adjacent capability, or stop investing in a feature that did not prove useful. This is how a scoped engagement becomes a sustainable improvement cycle rather than a one-time deliverable.

Where this capability connects

Voice AI depends on adjacent capabilities. Planning those connections early avoids a polished deliverable that cannot be adopted, measured, or supported. The right sequence may include research, design, implementation, security review, content, integrations, analytics, or team enablement. The required combination depends on the customer journey and the systems already in place.

Related capabilities: AI Agents · OpenClaw & n8n · Multi-Agent AI

Commercial Delivery Standards & Assurance

• Ultra-Low Latency Voice Pipeline (Deepgram + ElevenLabs + OpenAI Realtime)
• Twilio & SIP Telephony Phone Number Provisioning & Integration
• Live Cal.com / Google Calendar Real-Time Appointment Booking
• Natural Speech Interruption & Filler-Word Conversational Fluency
• Automated Post-Call Summaries, Sentiment Scores & CRM Updates

Transparent Package Tiers & Delivery Timelines

Frequently Asked Technical Questions

What should a business test before deploying a voice agent?

Test the real call types, handoff rules, consent and recording notices, integration failures, caller accessibility, and the quality-review process before expanding coverage.

What is included in the Voice AI project delivery?

All deliverables include custom architecture, complete Git repository source code access, automated testing, deployment staging, and 100% intellectual property ownership backed by our Delaware bilateral NDA.

What are the typical delivery timelines for Voice AI?

Estimated delivery timelines range from 6 to 25 business days depending on the selected package tier and statement of work.

How does Blunt Soft assure quality and post-launch support?

Every deliverable is verified through strict functional testing, security checks, and includes a 30-day post-launch bug warranty with defect remediation.