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The AI that replaces the interviewer, not just the phone call

A full voice-AI stack that dials respondents, conducts the interview, and reports results straight into Voxco

AI VoiceCATIMarket ResearchSIP/PBX
Year

2026

Duration

16 weeks

Industry

Market Research / AI

The AI that replaces the interviewer, not just the phone call
Starting position

Starting position

Starting position

  • Interviews requiring a live human interviewer

    Every CATI call staffed and conducted by a person

    100%
  • Concurrent interviews possible

    Scaling a campaign meant scaling the shift roster

    Bound by interviewer headcount
  • Interview availability

    No calling outside staffed hours

    Fixed shift hours
  • Callback / appointment handling

    An interviewer had to remember and redial

    Manual re-scheduling

Market size

Thousands of dialled cases per campaign, across concurrently running projects

CATI interviews run through FFIND's Voxco operation

Scope: FFIND market research campaignsSource: FFIND Voxco/iWeb sample volumes

Approx. budget

NDA

200,000 – 999,999 €

Budget breakdown

SIP/telephony engine & dialer (Go, Asterisk, NATS)30%
AI voice pipeline (STT, LLM, TTS, self-hosted on GPU)30%
Voxco/iWeb survey integration & disposition mapping25%
Operations dashboard & production hardening15%

Budget bucket per Clutch.co project cost category. Exact figures under NDA.

4-phase delivery

16 weeks

  1. 1

    Weeks 1-4

    SIP/PBX core + dialer architecture

  2. 2

    Weeks 5-9

    AI voice pipeline: speech-to-text, LLM answer matching, text-to-speech

  3. 3

    Weeks 10-13

    Voxco/iWeb survey driver, disposition codes & scheduler

  4. 4

    Weeks 14-16

    Operations dashboard, QA and production rollout

The Challenge

The interviewer was the bottleneck, not the phone system

FFIND runs CATI market research campaigns on Voxco, an industry-standard survey platform - but every single call still needed a human interviewer on the line to ask questions, understand answers, and record a result. That capped how many interviews could run at once, when they could run, and how fast a campaign could finish.

Campaign throughput was capped by interviewer headcount, not by how many lines could dial

Calls could only happen during staffed shift hours

An AI replacement had to run a real structured interview - not just transcribe a conversation

Results had to land back in Voxco using the exact disposition codes the rest of the operation already relies on

Our Solution

A voice-AI agent that plugs directly into the existing CATI workflow

We built a Go-based SIP/dialer engine paired with a self-hosted AI voice pipeline. The agent pulls the next case straight from Voxco's live sample, dials it, conducts the interview turn by turn against the real questionnaire, and writes the outcome back using Voxco's own disposition vocabulary - so the rest of FFIND's reporting and QA never has to know the interviewer was an AI.

Autonomous campaign dialer

Pulls the next respondent straight from the Voxco sample, keeps a configurable number of calls concurrently in flight, and idles/re-polls automatically when the sample runs low instead of ending the campaign.

Self-hosted AI voice pipeline

Speech-to-text, an LLM, and text-to-speech run on our own GPU infrastructure - no per-minute cloud voice API, full control over latency and data residency.

Live questionnaire driver

Speaks the actual Voxco questionnaire turn by turn, matches the caller's spoken answer to the right question option, rewrites terse survey-script text into natural spoken language, and re-asks rather than records when a transcript looks like a mishearing.

Voxco-compatible dispositions

Every call ends in the same disposition codes (interview completed, refusal, callback, wrong number, answering machine, do-not-call, etc.) FFIND's Voxco setup already expects.

Scheduler for callbacks & appointments

When a respondent asks to be called back at a specific time, the job is queued and automatically redialled at the agreed moment - no manual re-scheduling.

Operations dashboard

A management console for FFIND staff to watch calls live, review recordings and dispositions, manage projects, quotas and users.

What changed

How the interview delivery model changed

The phone call, the questionnaire and the reporting stayed the same - what changed is who is on the other end of the line.

Interview delivery

Before

Live human interviewer, every call

After

AI voice agent, questionnaire-aware

Removes the interviewer as the hard limit on campaign throughput.

Concurrent interviews

Before

Bound by interviewer headcount

After

Bound by telephony/infrastructure capacity

Scaling a campaign no longer means scaling a shift roster.

Calling hours

Before

Fixed staffed shifts

After

Scheduler-driven, including automatic callbacks

Calls and callbacks happen exactly when agreed, without a person remembering to redial.

Result reporting

Before

Manual disposition entry per call

After

Automatic, Voxco-compatible disposition codes

Existing QA and reporting pipelines keep working unchanged.

Investment → Operating CostNDA

Interview capacity that scales with infrastructure, not headcount

Ratio

Scales with telephony/GPU capacity, not headcount

campaign throughput is no longer capped by how many interviewers are on shift

Incremental revenue

Interviewer labor cost avoided per completed interview

modeled against standard CATI interviewer rates for an equivalent completed-interview volume

Investment

200,000 – 999,999 €

Payback period

Depends on sustained campaign volume; not yet independently audited

Method

Comparison of AI-agent operating cost (compute + telephony) against the standard cost of a live CATI interviewer per completed interview

Confidence

Medium - based on operating-cost modeling, not an audited financial report

This figure describes operating-cost avoidance, not FFIND revenue; exact volumes and figures are commercially confidential.

The Outcome

A CATI operation that can run without an interviewer on every call

The system is in production, dialling and interviewing directly against FFIND's Voxco sample. Live campaign volumes belong to FFIND; the figures below describe what changed operationally.

Interviews requiring a live human interviewer

Before

100%

After

Conducted end-to-end by the AI voice agent

Fully automatedFrom dial to disposition, no interviewer on the line

In production

Concurrent interviews in flight

Before

Bound by interviewer headcount

After

Configurable dialer concurrency

Decoupled from headcountCampaign throughput no longer tied to shift roster size

Per campaign

Disposition & result reporting

Before

Manual, per call

After

Automatic, Voxco-compatible codes

Fully automatedSame disposition vocabulary the rest of the operation already reports on

Every call

Callback / appointment follow-up

Before

Manual re-scheduling

After

Automatic redial at the agreed time

New capabilityRespondent-requested callbacks handled without operator intervention

Ongoing

Tech Stack
Go (Golang)
Asterisk PBX / SIP
NATS
Redis
PocketBase
Ollama (LLM)
Whisper / Parakeet (STT)
Chatterbox & Orpheus (TTS)
Voxco / iWeb API Integration
Next.js
We didn't want a chatbot bolted onto a phone line - we needed something that could actually run our questionnaire, the way our interviewers do. It dials our own Voxco sample, asks the real questions, and the results come back in the same format we already report on.

Operations Lead

FFIND

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