Case Studies

CASE STUDY 1 — Bailey (Sales Agent)

Use Case: Outbound Lead Generation, Appointment Setting

These results were delivered through our Managed AI Agent Service model—fully built, tuned, and monitored by our team.

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

Booked 34 qualified sales meetings in 30 days
4X increase in pipeline velocity
Freed up 2 human reps to focus exclusively on closing
Cost per qualified opportunity: 58% lower than SDR salary benchmarks
Client saw 6.8X ROI within the first quarter

“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.”

Client Quote

CASE STUDY 2 — Maia (Recruitment Agent)

Use Case: High-volume applicant pre-screening

These results were delivered through our Managed AI Agent Service model—fully built, tuned, and monitored by our team.

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

70% reduction in time spent screening
Average time-to-hire cut by 9 days
2X improvement in interview show-up rate
Recruiter satisfaction up due to reduced manual workload
Final candidates scored better on culture fit during onboarding

“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.”

Client Quote

CASE STUDY 3 — Shaina (Customer Support Agent)

Use Case: Collections, FAQs, and Payment Assistance

These results were delivered through our Managed AI Agent Service model—fully built, tuned, and monitored by our team.

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.”

Client Quote

CASE STUDY 4 — Kai (Sales Coaching Agent)

Sales Coaching, Call Review Automation, Rep Development

These results were delivered through our Managed AI Agent Service model—fully built, tuned, and monitored by our team.

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

2.4X increase in rep ramp-up speed
Coaching time per manager reduced by 67%
Average rep call score improved from 62 to 88 in 4 weeks
Increased conversion rate from lead to meeting by 36%
Kai-generated insights led to playbook update that lifted team-wide performance

“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.”

Client Quote