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We’re documenting outstanding success stories.
We’re currently turning our projects into in-depth case studies. In the meantime, explore examples of our work across different industries. Want to know when new case studies go live? Subscribe to our newsletter. You’ll also get AI trends and updates, tool reviews, and key research insights.
Example Projects
Challenge:
Mid-size law firm spends 8-12 hours preparing each new client proposal, mostly assembling standard language and past work examples.
What We Built:
AI system that generates first-draft proposals from past work, customizes language based on practice area and client industry, and assembles relevant case studies.
Results:
Proposal preparation time reduced from 10 hours to 2 hours. Partners spend time refining strategy, not copying and pasting.
Challenge:
Consultants spend 15-20 hours per engagement reading industry reports, competitive analyses, and market research before beginning client work.
What We Built:
AI system that ingests research documents, extracts key findings, identifies themes, and creates synthesis documents with source citations.
Results:
Research phase reduced from 20 hours to 6 hours. Consultants review synthesized information and apply strategic thinking instead of manual reading.
Challenge:
Property management company fields 200+ routine tenant inquiries per week (lease questions, maintenance requests, payment issues) via email, text, and phone.
What We Built:
AI communication system that handles routine inquiries, escalates complex issues to humans, and maintains consistent response times under 30 minutes.
Results:
87% of routine inquiries handled by AI. Staff focus on complex tenant issues and relationship management. Response time improved from 4 hours to 22 minutes.
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Challenge:
12-location primary care network averaging 18 minutes per patient intake, causing delays and staff burnout.
What We Built:
HIPAA-compliant digital intake system with AI validation, insurance verification, and EHR integration. Patients complete intake before arrival; staff verify and import.
Results:
Intake time reduced to 6-8 minutes. Front desk staff redeployed to patient coordination and care navigation. Patient wait time reduced by 12 minutes on average.
Compliance:
Full HIPAA compliance maintained, BAA executed, audit trail documented
Challenge:
Physicians spending 2-3 hours nightly completing visit documentation, leading to burnout and reduced patient time.
What We Built:
AI documentation assistant that generates draft notes from visit recordings, includes proper medical terminology, and formats for EHR import. Physicians review and approve.
Results:
After-hours documentation time reduced from 2.5 hours to 45 minutes. Patient face-to-face time increased by 15%. Physician satisfaction improved significantly.
Compliance:
All recordings stored in HIPAA-compliant environment, physician maintains final authority over all documentation
Challenge:
Solo practitioner losing 10+ hours weekly to scheduling calls, insurance verifications, and appointment logistics.
What We Built:
AI scheduling system that handles appointment requests, verifies insurance, sends reminders, and manages reschedules via HIPAA-compliant communication channels.
Results:
Scheduling time reduced by 85%. Practitioner added 4 additional client slots per week. No-show rate reduced from 18% to 7% due to improved reminder system.
Compliance:
All patient communication through BAA-covered channels
Challenge:
Series A SaaS company facing support ticket volume growth (400% in 6 months) with only 2 support team members. Response time slipping from 2 hours to 18 hours.
What We Built:
AI support system that handles tier-1 questions (billing, account management, password resets, feature questions), escalates technical issues to humans, and maintains conversation history for seamless handoffs.
Results:
71% of tickets fully resolved by AI. Average response time reduced to 8 minutes. Support team focuses on complex technical issues and customer success.
Investor Impact:
Demo'd AI support capabilities in board meeting, used as proof of technical sophistication for Series B fundraising.
Challenge:
Seed-stage fintech with 3-person sales team spending 50% of time on manual CRM updates, lead research, and email follow-ups instead of actual selling.
What We Built:
AI sales operations system that qualifies inbound leads, researches prospects on LinkedIn and company websites, updates CRM automatically, generates personalized outreach emails, and schedules follow-ups.
Results:
Sales team time on non-selling activities reduced from 50% to 15%. Meeting volume increased by 40%. CRM data quality improved significantly.
Investor Impact:
Demonstrated efficient scaling of sales motion without headcount increases
Challenge:
Pre-seed consumer app needed to produce 15-20 social media posts, 4-6 blog articles, and 30+ email variations weekly with 1.5-person marketing team.
What We Built:
AI content production system with brand voice guidelines, template library, and approval workflows. Generates drafts for all content types; marketing team reviews and refines.
Results:
Content production time reduced by 60%. Publishing frequency doubled. Marketing team focuses on strategy and high-value creative work instead of production.
Challenge:
Marketing ops director at $500M company spending 15 hours monthly compiling campaign performance reports from multiple sources (GA, HubSpot, LinkedIn, Salesforce) for executive review.
What We Built:
AI reporting system that pulls data from all sources, generates standardized performance summaries, identifies trends, and creates executive-ready presentations.
Results:
Report compilation time reduced from 15 hours to 2 hours. More frequent reporting (weekly vs monthly) provides faster feedback for campaign adjustments.
Executive Impact:
Used success to secure $150K budget for broader marketing automation initiative
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Challenge:
RevOps leader at mid-market SaaS company facing 40% error rate in CRM data, impacting forecasting accuracy and pipeline visibility. Sales team doesn't prioritize data entry.
What We Built:
AI system that monitors CRM data quality, prompts sales team to correct missing/inaccurate information, auto-fills certain fields from meeting notes and email, and flags forecast risks based on data patterns.
Results:
CRM data accuracy improved from 60% to 91%. Forecast variance reduced by 35%. Sales team spends 70% less time on manual data entry.
Executive Impact:
CFO cited improved forecast accuracy in board presentation; RevOps leader promoted to VP
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Challenge:
HR ops manager at 800-person company spending 6-8 hours per new hire on onboarding logistics: system access requests, equipment orders, training schedules, compliance documentation.
What We Built:
AI onboarding coordinator that triggers automated workflows based on role and department, tracks completion status, sends reminders to stakeholders, and generates compliance reports.
Results:
Onboarding coordination time reduced from 7 hours to 1.5 hours per hire. New employee time-to-productivity improved by 20%. Zero compliance documentation gaps in 6 months.
Executive Impact:
CHRO approved expansion to offboarding and internal transfers
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We design, validate, and deploy focused AI systems that improve real workflows in 2-6 weeks.
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