Real Problems. Real Fixes.
Every project below started with someone saying "there has to be a better way." Here's what we built for them.
Business Process Fixes
Automations that replace tedious manual workflows.
Design Spec Sheet Manager
The Problem
Interior designers were spending hours manually building product specification sheets for each project. Every item needed dimensions, pricing, vendor info, lead times, and images, all copied from different supplier websites and PDFs into a spreadsheet.
What We Built
We built an AI-powered spec sheet system that eliminates the copy-paste grind. Designers drop in a link or upload a vendor PDF, and the AI extracts dimensions, pricing, lead times, images, and sourcing details automatically. It builds a growing product library that gets smarter with every project, suggests alternatives when items are discontinued, and generates polished spec sheets ready to share with clients and tradespeople. No more toggling between supplier websites and spreadsheets.
The Result
Spec sheet preparation went from 3 hours per project to about 20 minutes. Designers now spend their time designing instead of copy-pasting from catalogs.
- ✓ AI extracts product details from vendor websites and PDFs -- no manual data entry
- ✓ Auto-generates polished spec sheets for clients and trades
- ✓ Detects pricing changes and suggests alternatives when products are discontinued
- ✓ Designers reclaimed 10+ hours per week
Invoice Reconciliation
The Problem
A consulting firm with multiple clients and contractors was spending two full days every month reconciling time tracking data with their accounting system. Every invoice required manually checking hours, applying different billing rates per person per project, correcting tax rates by province, and mapping revenue to the right accounts.
What We Built
We built an AI-powered invoicing system that replaces two full days of manual data entry every month. It pulls hours from the time tracking system, matches each person to the correct billing rate per project, applies the right tax rules based on client location, maps revenue to the correct accounts per consultant, and pushes completed invoices to the accounting system. But the real magic is the two-layer validation. First, the AI flags mismatched hours, incorrect tax rates, and missing line items. Then a second AI reviews the results against a full year of historical patterns -- comparing this month's invoices to what's come before and surfacing anything that looks off. Between the two passes, the human reviewer gets a clean interface that brings everything they need to scan and confirm into one view. No digging through spreadsheets, no toggling between systems. Just review, approve, and move on -- knowing two AI systems already checked the work.
The Result
Monthly invoicing went from two painful days to 45 minutes of review and approval. Billing errors dropped to near zero.
- ✓ AI matches each person to the correct billing rate per project -- no lookup tables or manual entry
- ✓ Dual-layer AI validation: one checks the rules, a second compares against a year of historical patterns
- ✓ Human review interface surfaces only what needs attention -- no spreadsheet digging
- ✓ Two days of monthly invoicing reduced to 45 minutes of review and approval
Project Burn-Down Reports
The Problem
A services firm billed hourly across dozens of active projects but had no real-time visibility into how hours were being consumed. By the time someone noticed a project was over budget, it was too late to course-correct. Budget conversations with clients were reactive and uncomfortable.
What We Built
We built AI-powered project dashboards that do more than show where you've been -- they predict where you're headed. The system pulls live time tracking data and displays burn-down charts for every active project, but the AI layer is what makes it different. It analyzes pace patterns across the team, flags projects that are trending toward overrun weeks before they hit the threshold, and generates plain-language weekly summaries so managers don't have to interpret charts. When a project crosses 75% of its budget, the alert doesn't just say 'you're running low' -- it tells you who's burning hours fastest and which tasks are eating more than expected. Project managers go into client conversations with data and a story, not a surprise invoice.
The Result
Budget overruns are now caught weeks earlier. Project managers have proactive conversations with clients instead of delivering surprise invoices.
- ✓ AI predicts budget overruns weeks before they happen based on pace patterns
- ✓ Plain-language weekly summaries -- no chart interpretation needed
- ✓ Alerts tell you who's burning hours fastest and which tasks are over-consuming
- ✓ Exportable reports for proactive client budget conversations
Meeting Notes Autopilot
The Problem
A team was holding 15+ client meetings per week, and meeting notes were either never written, written days later from memory, or so verbose nobody read them. Action items fell through the cracks constantly.
What We Built
We built a pipeline that takes meeting recordings, generates concise summaries with clearly tagged action items, and emails them to all attendees within minutes of the meeting ending. The summaries highlight decisions made, next steps with owners, and open questions that need follow-up.
The Result
Every meeting now has professional notes delivered within 5 minutes. Action item follow-through improved dramatically because owners are named and deadlines are visible.
- ✓ Summaries delivered to attendees within 5 minutes of meeting end
- ✓ Action items automatically tagged with owners and deadlines
- ✓ Distinguishes between decisions, next steps, and open questions
- ✓ Team stopped losing track of commitments made in meetings
Enterprise-Grade Solutions
Bigger systems for teams that need serious horsepower.
Revenue Forecasting
The Problem
A growing company was forecasting revenue using a combination of gut feeling and an outdated spreadsheet that nobody trusted. Decisions about hiring, investments, and capacity were based on numbers that were often wrong by 20% or more.
What We Built
We built a forecasting system that replaces the gut-feel spreadsheet with live data from billing, active contracts, and pipeline deals. Every month the system captures a snapshot -- what was forecasted versus what actually landed. Over time, AI will use that growing history to spot patterns, flag unrealistic projections, and help leadership make sharper decisions about hiring, capacity, and investment. The system is designed to get smarter the longer it runs. Right now it pulls real numbers instead of guesses. Six months from now it'll tell you why your Q3 forecast is probably too optimistic based on how similar quarters have actually played out.
The Result
Revenue forecasts went from guesswork to within 5% accuracy. Leadership now makes hiring and investment decisions with confidence instead of hope.
- ✓ Replaces spreadsheet forecasting with live billing, contract, and pipeline data
- ✓ Captures forecast-vs-actual snapshots every month to build a learning dataset
- ✓ Designed for AI to analyze patterns and improve projections over time
- ✓ Updates automatically as deals close, slip, or expand
CRM Auto-Updater
The Problem
A sales team's CRM was perpetually out of date. Reps were supposed to log meeting notes, update deal stages, and record next steps after every call, but they rarely did. Pipeline reviews were exercises in fiction because the data couldn't be trusted.
What We Built
We built a system that listens to meeting recordings, extracts key details (deal stage changes, budget discussions, next steps, competitor mentions), and updates the CRM automatically. Reps get a quick summary to review, but the heavy lifting is done for them.
The Result
CRM data accuracy jumped from roughly 40% to 95%. Pipeline reviews became genuinely useful because the numbers reflect reality, not optimistic guesses.
- ✓ Extracts deal details from meeting recordings automatically
- ✓ Updates deal stages, contacts, and next steps in the CRM
- ✓ Reps review a summary instead of doing manual data entry
- ✓ Pipeline accuracy went from ~40% to 95%
Proposal Assembly System
The Problem
A consulting firm was writing every proposal from scratch, even though 60-70% of the content was reusable. Senior staff spent entire weekends assembling proposals, and the quality was inconsistent because different people wrote in different styles.
What We Built
We built a knowledge base containing the firm's case studies, team bios, methodologies, and boilerplate sections, then layered an AI drafting system on top. The AI pulls relevant pieces from the knowledge base and assembles a first draft tailored to each opportunity. Senior staff review and refine instead of writing from zero.
The Result
Proposal turnaround dropped from two weeks to two days. Quality became consistent across all proposals, and senior staff reclaimed their weekends.
- ✓ Centralized knowledge base with case studies, bios, and methodologies
- ✓ AI assembles tailored first drafts from the knowledge base
- ✓ Consistent quality and voice across all proposals
- ✓ Turnaround time reduced from 2 weeks to 2 days
RFP Response Workflow
The Problem
Every time a Request for Proposal arrived, the team went into fire-drill mode. Someone would manually read through 50+ pages, extract requirements, assign sections to different writers, and then struggle to assemble a coherent response before the deadline. Requirements were missed. Formatting was inconsistent. Deadlines were tight.
What We Built
We built a workflow that ingests an RFP document, automatically extracts and categorizes every requirement, maps them to the firm's existing capabilities and past responses, and generates section drafts that writers can refine. A compliance checklist tracks every requirement to ensure nothing is missed.
The Result
RFP response time was cut in half. The compliance checklist eliminated missed requirements entirely. Win rate improved by roughly 30% because responses were more thorough and polished.
- ✓ Automatically extracts and categorizes requirements from RFP documents
- ✓ Maps requirements to existing capabilities and past responses
- ✓ Generates section drafts for writers to refine
- ✓ Compliance checklist ensures zero missed requirements
Everyday Problems
Personal and small-business fixes that save real time every week.
Family Calendar Assistant
The Problem
Two working parents, three kids, and a shared inbox drowning in school emails, sports schedules, and appointment reminders. Events were getting missed because nobody had time to read every email and manually add dates to the calendar.
What We Built
We built an AI assistant that monitors the family inbox, extracts dates and events from emails, and adds them to a shared family calendar automatically. It handles school newsletters, sports league updates, appointment confirmations, and even birthday party invites. Duplicates are detected and merged. Conflicts trigger a text alert.
The Result
Zero missed events in the first three months. The family went from spending 30 minutes a day scanning emails to just glancing at their calendar each morning.
- ✓ Reads and parses emails from 15+ different senders automatically
- ✓ Detects scheduling conflicts and sends instant text alerts
- ✓ Handles messy formats like newsletter PDFs and image-based flyers
- ✓ Family stopped missing school events entirely
Home Office Expense Calculator
The Problem
A self-employed professional was leaving money on the table every tax season. Tracking business-use-of-home expenses meant digging through utility bills, mortgage statements, and insurance documents once a year, and something always got missed.
What We Built
We built an AI-powered expense tracker that connects to their accounts, reads utility bills, mortgage statements, insurance documents, and property tax notices -- even scanned PDFs and photos of paper bills. The AI categorizes each expense, determines what qualifies as a business deduction, calculates the business-use percentage based on square footage, and keeps a running tally year-round. No more manual data entry or guessing what counts. At tax time, it generates a clean summary ready for their accountant.
The Result
Found $2,400 in deductions that had been missed in previous years. Tax prep time dropped from a full weekend to 15 minutes of review.
- ✓ AI reads and categorizes expenses from statements, PDFs, and even photos of paper bills
- ✓ Calculates business-use percentage based on actual square footage
- ✓ Generates accountant-ready summaries at tax time
- ✓ Runs year-round so nothing gets missed
Email Voice Trainer
The Problem
A professional was spending 2+ hours daily writing emails. They tried AI assistants, but every draft sounded generic and corporate, nothing like their actual voice. They'd spend almost as long editing the AI output as they would writing from scratch.
What We Built
We built a voice training system that analyzed hundreds of their sent emails to learn their exact writing patterns: sentence length, vocabulary, tone shifts between casual and formal contexts, even their preferred greetings and sign-offs. The AI now drafts emails that match their style so closely that minor edits are all that's needed.
The Result
Email drafting time dropped by 75%. Colleagues and clients can't tell which emails were AI-assisted, because the voice is genuinely theirs.
- ✓ Trained on hundreds of real sent emails to capture authentic voice
- ✓ Adapts tone between casual internal and formal client emails
- ✓ Learns preferred greetings, sign-offs, and sentence patterns
- ✓ Email writing time dropped from 2+ hours to 30 minutes daily
Volunteer Training Hub
The Problem
A community organization relied on a small team of volunteers to run audio-visual equipment for weekly events. When experienced volunteers moved on, new ones had no documentation to learn from. Every transition meant weeks of trial-and-error and frustrated audiences.
What We Built
We used AI to rapidly build a comprehensive training hub tailored to the organization's specific equipment and workflows -- what would have taken weeks of writing was done in days. Every page has a simple feedback button so volunteers can flag stale instructions, suggest improvements, or note something confusing while it's fresh in their minds. New volunteers are especially valuable here -- they see things with fresh eyes that experienced people gloss over. Feedback flows into the AI system, and management can review suggestions and approve updates with one click. After every live event, an AI-powered debrief system collects feedback from the crew, generates a summary report, and emails it to the management team automatically. No more chasing people for post-event notes. The system maintains a living backlog of improvements and flags high-priority incidents where equipment needs repair or replacement. The documentation never goes stale because the AI keeps it current from two directions: real-time volunteer feedback and post-event debriefs.
The Result
New volunteers went from needing 6-8 weeks of shadowing to running the system confidently within 2 weeks. Equipment issues dropped by 70% because troubleshooting guides caught problems before they became visible to the audience.
- ✓ AI-generated documentation built in days instead of weeks of manual writing
- ✓ One-click feedback on every page -- volunteers flag issues, AI drafts the fix, management approves
- ✓ Automated post-event debriefs summarize crew feedback and email management
- ✓ Flags high-priority equipment issues needing repair or upgrade
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