Before and after.
What a business looks like before we build its AI team — and after. These are reference builds: the system designs we deploy, shown against the workflows they replace, with representative outcomes for each.
Straight with you: These are illustrative reference builds, not client testimonials — we're early, and we'd rather show you exactly what we build than dress up borrowed logos. The numbers are representative of what these systems produce; we scope a specific ROI projection for your business on the strategy call.
Boutique Corporate Law Firm
60 hrs/wk saved
Paralegals spent 60+ hours a week manually reading through discovery PDFs and copy-pasting relevant clauses into summary documents.
Attorneys upload a document, wait 45 seconds, and get a formatted brief of every relevant clause and contradiction — automatically.
Read the full breakdown+
Before
Paralegals spent 60+ hours a week manually reading through discovery PDFs, highlighting relevant clauses, and copy-pasting into summary Word documents. High burnout, high margin of error.
After
Secure local vector database architecture. Attorneys upload a PDF, wait 45 seconds, and receive a perfectly formatted, paginated brief of all relevant clauses and contradiction risks.
Results are illustrative. Actual outcomes depend on document volume, data readiness, and business complexity.
B2B Marketing Software
3× faster support
A 4-person support team struggled to keep up with technical API questions from users. Average time to first response: 4 hours.
An AI agent resolves common questions instantly. Bugs get automatically tagged, summarized, and routed to an engineer — no human triage needed.
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Before
Support team spent most of the day answering the same tier-1 API questions. Complex bugs were getting lost in the queue. Average response time: 4 hours.
After
AI agent handles informational queries in under 5 seconds. When it detects a bug, it writes a summary, tags it, and routes it to engineering. Support team only touches what needs a human.
Results are illustrative. Actual outcomes depend on ticket volume, documentation quality, and team setup.
Apparel Brand
22% more revenue
Marketing team manually downloaded Shopify CSVs every Friday, sorted for VIP buyers, and loaded them into email campaigns by hand.
An automated pipeline detects purchasing patterns, tags high-value customers, and triggers personalized campaigns — without anyone touching a spreadsheet.
Read the full breakdown+
Before
Marketing team was manually downloading Shopify CSVs every Friday, sorting them to find high-value buyers, and manually loading them into email flows. Campaign timing was always delayed.
After
Continuous sync. An algorithm detects purchasing behavior in real time, tags customers by lifetime value, and triggers the right campaign automatically — no Friday manual work, no delays.
Results are illustrative. Actual outcomes depend on business complexity, data readiness, and existing tech stack.
Residential Brokerage
12 hrs/day reclaimed
Agents manually checked 5 listing platforms for new inquiries throughout the day. Hot leads sometimes went 3-4 hours without a response — enough time to lose them.
A single AI inbox monitors all platforms simultaneously, qualifies each lead in under 60 seconds, and routes hot prospects directly to an agent's phone.
Read the full breakdown+
Before
Team cycled through Zillow, Realtor.com, and 3 other platforms manually. Leads from evenings and weekends sat cold until Monday. Conversion from inquiry to appointment was under 8%.
After
AI responds to every inquiry in under 60 seconds, qualifies interest, captures budget and timeline, and books a showing directly into the agent's calendar — 24/7, including weekends.
Results are illustrative. Actual outcomes depend on lead volume, market conditions, and team setup.
Multi-Provider Medical Clinic
40% fewer no-shows
Front desk staff called every patient the day before their appointment to confirm. Missed calls meant no-shows — each empty slot cost $300–$500.
Automated system sends personalized texts 48 hours and 2 hours before each visit, handles reschedules, and updates the calendar — zero staff time required.
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Before
Front desk spent 2 hours each morning calling the next day's patients. Many didn't answer. No-show rate was 22%. Empty appointment slots were effectively lost revenue with no recovery system.
After
Patients receive an automated text 48 hours and 2 hours before their visit. A two-way SMS flow handles rescheduling and fills cancellations from a waitlist — automatically, with no staff involvement.
Results are illustrative. Actual outcomes depend on patient volume, EHR compatibility, and practice type.
Mid-Sized CPA Firm
80% less data entry
Staff manually rekeyed client financial data from bank PDFs and statements into QuickBooks. One client's monthly close took three full days.
Documents are uploaded to a secure portal. AI extracts, categorizes, and syncs every transaction — monthly close dropped from 3 days to 6 hours.
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Before
Staff read PDFs, typed numbers into QuickBooks, and built reconciliation spreadsheets by hand. The firm was limited in how many clients it could take on. Senior staff spent hours on clerical work.
After
Clients upload documents to a portal. AI extracts and structures every line item, maps it to the chart of accounts, and syncs it directly into QuickBooks — reviewable before posting.
Results are illustrative. Actual outcomes depend on document complexity, chart of accounts structure, and client volume.
Technical Recruiting Agency
5× more applicants screened
Recruiters spent 3–4 hours per open role manually reading resumes and emailing first-round screening questions. Positions stayed open weeks longer than necessary.
AI screens every application against a custom rubric, sends tailored questions to candidates, scores responses, and surfaces the top 10% — recruiters only see finalists.
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Before
With 15 open roles and 80+ applicants each, recruiters were reading 1,200+ resumes a week. Most candidates never heard back. Time-to-fill averaged 34 days.
After
Every applicant gets a structured AI screening within 2 hours of applying. Qualified candidates receive personalized role-specific questions. Recruiters review a scored shortlist — not a pile of PDFs.
Results are illustrative. Actual outcomes depend on applicant volume, role complexity, and existing ATS setup.
3-Location Dining Group
22 hrs/wk reclaimed
Operations manager manually pulled sales, labor, and waste data from 3 POS systems every Monday morning and built a weekly report by hand — a 4-hour process.
A nightly pipeline pulls data from all 3 locations automatically. A formatted operations report lands in the inbox every Monday at 6am — no one touches it.
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Before
Ops manager logged into 3 separate POS dashboards, exported CSVs, manually combined them in Excel, built charts, and emailed the weekly report. Took 4 hours every Monday — and one bad export could break the whole thing.
After
Nightly sync pulls sales, labor, and waste data from all 3 locations. An AI-written summary highlights anomalies, flags underperforming shifts, and emails the full formatted report every Monday at 6am.
Results are illustrative. Actual outcomes depend on POS compatibility, data quality, and reporting complexity.
Residential Property Manager
70% fewer urgent calls
Maintenance requests came in via text, email, and voicemail to one overloaded phone number. Urgent issues got buried next to routine ones. Tenants waited days for updates.
A triage bot receives all requests through a single link, classifies urgency instantly, routes critical issues to on-call staff, and sends tenants automatic status updates.
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Before
Property manager received texts, calls, and emails at all hours. A broken pipe and a squeaky door sat in the same inbox. Staff triaged manually, often missing real emergencies on weekends.
After
All requests go through one intake link. AI classifies severity, dispatches contractors for emergencies immediately, batches routine requests for weekly scheduling, and keeps tenants updated without a single call.
Results are illustrative. Actual outcomes depend on unit count, contractor network, and existing maintenance workflows.
Independent Insurance Agency
35% higher close rate
Agents followed up on web leads with a single email, then moved on. Most leads went cold after day 3. There was no system to re-engage stale quotes or track where prospects dropped off.
A 60-day automated nurture sequence personalizes follow-ups by coverage type, surfaces hot leads when engagement spikes, and archives cold ones — agents only touch the ready buyers.
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Before
Web form leads got one generic “thank you for your inquiry” email. If the prospect didn’t reply, they were effectively lost. Agents had no visibility into where leads were in the funnel.
After
Every lead enters a 60-day personalized email and SMS sequence based on coverage type. An engagement scoring model surfaces warm leads to agents in real time. Cold leads archive automatically after the sequence ends.
Results are illustrative. Actual outcomes depend on lead quality, sequence length, and product type.
Performance Marketing Agency
3× client capacity
Account managers spent 2–3 days per month per client manually pulling Google Ads, Meta, and Analytics data, writing commentary, formatting decks, and emailing reports.
Every client report generates automatically on the 1st of each month — data pulled, analyzed, AI-written commentary, formatted as a PDF, and emailed without anyone touching it.
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Before
With 18 active clients, account managers spent the first week of every month doing nothing but pulling metrics, building slides, and writing performance commentary. Growth was bottlenecked by reporting overhead.
After
A scheduled pipeline pulls all platform data on the last day of each month, feeds it into an AI that writes client-specific commentary, formats a branded PDF, and emails it directly to the client — zero manual work.
Results are illustrative. Actual outcomes depend on client count, platform mix, and reporting complexity.
Contractor Staffing Firm
90 hrs/mo reclaimed
HR team manually sent offer letters, collected tax forms, coordinated background checks, and chased down signatures — every contractor onboarding took 3–5 days and constant follow-up.
New contractors receive one link. They complete the entire onboarding flow — documents, tax forms, background check authorization — in under 15 minutes. HR only reviews the completed file.
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Before
HR sent 6–8 emails per contractor, manually tracked which forms were returned, followed up on missing signatures, and coordinated with a background check vendor by email. Onboarding averaged 4 days per hire.
After
One onboarding link handles everything — identity verification, DocuSign contracts, tax form collection, and background check authorization — in a single guided flow. HR receives a complete file when it’s done.
Results are illustrative. Actual outcomes depend on contractor volume, document complexity, and background check turnaround.
Become our next before-and-after.
If you're spending hours on tasks that could run on autopilot, book a call and we'll map the AI team we'd build for you — with a real ROI projection.