Case Studies

CASE STUDY 1 — Bailey (Sales Agent)

Use Case: Outbound Lead Generation, Appointment Setting

Problem:

A lean B2B SaaS team struggled to scale its outbound sales. Their solo SDR could only make 30–40 calls per day, averaging 8 meetings per month. Worse, burnout and turnover were a constant threat—each new hire required 6–8 weeks of ramp time, delaying growth.

Solution

VC AI deployed Bailey, the Sales AI Agent, trained on the team’s value prop and objection handling scripts. Bailey handled 200+ calls per day using a structured permission-based opening, pain funnel discovery, and BANT qualification. Calls were logged, scored, and escalated only when they met preset criteria.

Results

“Bailey didn’t just scale our outreach—she gave our closers a running start every morning. It’s like hiring your best SDR… and duplicating them instantly.”

CASE STUDY 2 — Maia (Recruitment Agent)

Use Case: High-volume applicant pre-screening

Problem:

A leading BPO with 1,000+ monthly applicants faced long delays in hiring. Recruiters were drowning in resumes and phone screens, often spending 10+ minutes per call. Applicants ghosted regularly, and quality-of-hire metrics were slipping.

Solution

We activated Maia, the Recruitment AI Agent, to pre-screen candidates through voice interviews. She asked standardized role-fit questions, scored responses using dynamic criteria, and flagged only the top 30% for human review. Custom logic filtered based on location, availability, and communication skills.

Results

“We used to lose great candidates because we couldn’t move fast enough. Maia changed that. Now our team gets only the most serious and qualified applicants—ready to go.”

CASE STUDY 3 — Shaina (Customer Support Agent)

Use Case: Collections, FAQs, and Payment Assistance

Problem:

A digital lending platform was overwhelmed with repayment inquiries, account issues, and delay requests. Human agents were stretched thin, response times exceeded SLA, and customer satisfaction was declining. The cost of each live agent call continued to rise.

Solution

Shaina, the AI Support Agent, was deployed to handle payment reminders, resolve FAQs, and assist with account troubleshooting. With empathetic voice modulation and structured follow-ups, Shaina resolved 80%+ of Tier 1 inquiries autonomously. She only escalated sensitive cases to live agents—with full call summaries attached.

Results

“Shaina doesn’t just handle volume—she handles people. Our users feel heard, and our team finally has breathing room. It’s the best support investment we’ve made.”

CASE STUDY 4 — Kai (Sales Coaching Agent)

Sales Coaching, Call Review Automation, Rep Development

Problem:

The EdTech company had a fast-growing SDR team, but performance varied wildly across reps. Managers lacked time to review calls in depth, and feedback often came too late to correct course. Coaching sessions were reactive, not proactive—and top performers remained “black boxes.”

Solution

They implemented Kai, the AI Sales Coaching Agent. Kai automatically analyzed every outbound call using natural language processing to detect sales stage, tone, objection handling, and adherence to the company’s playbook (BANT, surface pain, budget). It generated coaching feedback per rep and flagged coachable moments in real time.

Results

“Kai gave us something we never had before—instant, unbiased coaching that actually made our reps better every week. Our managers finally had time to lead, not just listen.”