Custom AI Tools — San Francisco Bay Area San Francisco Bay Area & Remoteamp; Remote
Stop paying for software
that doesn't fit.
Every business has workflows that no off-the-shelf SaaS handles properly. You end up duct-taping three tools together, training people on workarounds, and paying monthly fees for features you don't use. I build the tool your business actually needs — and you own it when I'm done.
What I build
Automated document processing pipelines
Your team spends hours every week pulling data out of PDFs, invoices, contracts, or intake forms — copying numbers into spreadsheets, flagging exceptions by hand. I build pipelines that ingest those documents, extract the data with AI, validate it against your business rules, and push it straight into your existing systems. The humans review edge cases. The machine handles the other 90%.
AI-powered customer service routing
Tickets pile up. The urgent ones get buried under password resets. Your best people waste time on problems a script could solve. I build routing systems that read incoming requests, classify urgency and intent, auto-resolve the straightforward ones, and send the rest to the right person with full context already attached. Response times drop. Escalations drop faster.
Internal knowledge bases that actually work
Every company has a Confluence or Google Drive graveyard — thousands of pages that nobody searches because the search is garbage. I build knowledge systems backed by vector search and retrieval-augmented generation. Your team asks a question in plain English and gets an answer sourced from your actual documentation, SOPs, and past decisions. Not a chatbot that hallucinates. A search tool that cites its sources.
Automated report generation
Someone on your team spends every Monday morning pulling numbers from three dashboards, pasting them into a slide deck, and writing the same summary with different numbers. I build systems that pull from your data sources, generate the narrative, format the report, and deliver it before anyone gets to the office. Weekly ops reports, investor updates, compliance filings — whatever takes time and follows a pattern.
Data extraction from unstructured sources
You have data locked in emails, scanned documents, handwritten forms, or legacy systems with no API. Your team re-keys it manually. I build extraction pipelines that use OCR, NLP, and custom-trained models to pull structured data out of messy sources and feed it into your databases. No more re-keying. No more transcription errors. No more hiring temp workers for data entry backlogs.
Custom CRMs with AI intelligence
Salesforce costs a fortune and your team uses 10% of it. HubSpot almost works but the reporting is wrong for your sales cycle. I build CRMs tailored to how your business actually sells — with AI that scores leads based on your historical close data, drafts follow-up emails that match your voice, and flags deals that are going cold before your reps notice. Built on your terms, integrated with the tools you already use.
How a custom build works
Week 1
Discovery — mapping your manual processes
I sit with your team and watch how work actually gets done. Not what the process doc says — what people actually do. Where they copy-paste between tabs. Where they eyeball a number and make a judgment call. Where they email someone to ask a question that should be answered by a system. By the end of the week, I have a clear map of what gets automated, what stays manual, and where AI adds real value versus where a simple script does the job.
Weeks 2-3
Prototype — working proof of concept against your real data
Not a mockup. Not a slide deck with arrows. A working system processing your actual data in your actual environment. If the AI is going to misclassify something, I want to see it now — when it costs a day to fix — not three months from now when the whole system is built on a bad assumption. You see it work, you give feedback, we iterate.
Weeks 4-7
Production — error handling, monitoring, user training
This is where prototypes usually die and where 25+ years of engineering experience pays for itself. Fallback paths for when the AI gets it wrong. Monitoring dashboards so you know the system is healthy without checking manually. Cost controls on API usage. Audit logs for compliance. User training so your team knows how to use the tool and how to handle the cases the AI flags for human review.
Handoff
You own the code. No vendor lock-in.
Full source code in your repository. Documentation your developers can actually follow. Runbooks for every failure mode I've seen during development. Your team trained to maintain and extend the system. There's no recurring license fee. No monthly charge to keep the lights on. No dependency on me to keep things running. If you want ongoing support, I'm available. If you don't, the system keeps working.
Build vs. buy — when custom makes sense
Off-the-shelf software is the right call 80% of the time. But there are situations where buying creates more problems than it solves. Custom AI tooling makes sense when:
Your workflow is unique to your industry
SaaS products are built for the average case. If your process was shaped by regulations, legacy systems, or hard-won domain knowledge that your competitors don't have, no generic tool is going to support it without heavy customization. At that point, you're paying SaaS prices for a tool you've bent into something it was never designed to be.
SaaS costs are scaling faster than your revenue
Per-seat pricing, per-transaction fees, overage charges. The SaaS business model is designed to grow with you — which sounds good until you realize their revenue grows faster than your margin. A custom tool has a fixed build cost and minimal ongoing infrastructure expenses. At scale, the math always favors owning.
You need to own the data pipeline
When your data flows through a third party's servers, you're at the mercy of their security practices, their uptime, their API changes, and their business decisions. If they get acquired, raise prices, or sunset a feature, your operations are at risk. Owning the pipeline means your data stays in your infrastructure, under your control, on your terms.
Off-the-shelf tools require five workarounds to do what you need
Zapier chains. CSV exports piped into Google Sheets formulas. Chrome extensions that scrape data from one tab and paste it into another. If your team has built a Rube Goldberg machine to make a SaaS product do something it wasn't designed for, you don't have a solution — you have technical debt disguised as a workflow. A custom build replaces the whole chain with something that was designed for your actual job.
What you own when it's done
When the project ships, everything transfers to you. No strings, no subscriptions, no lock-in.
Source code
Every line, in your Git repository, under your control. Written in standard frameworks your team already knows or can learn — not proprietary abstractions that require my involvement to modify.
Documentation
Architecture decisions and why they were made. API references. Data flow diagrams. Not the kind of docs that were generated to check a box — the kind your next developer will actually read when they need to change something.
Runbooks
Step-by-step procedures for every failure mode I encountered during development. What to check when the system alerts. How to restart components. When to escalate. Your team doesn't need to reverse-engineer the system when something goes wrong at 2 AM.
A trained team
I walk your people through the system until they're comfortable maintaining and extending it. Not a one-hour handoff call — actual working sessions where they make changes, ask questions, and build confidence with the codebase.
No recurring license fee. No monthly maintenance contract required. No dependency on me to keep the lights on. You pay once for the build and you own it forever.
See it in action
Case study
ClaimHawk — autonomous dental insurance claims
A custom AI tool that reads insurance EOBs, extracts denial codes, drafts appeal letters, and resubmits claims without human intervention. Built for the dental industry because no off-the-shelf RCM software handled the full cycle autonomously. 67% fewer denials. 4x faster payments. This is what a custom AI tool looks like when it's built for a specific business problem.
Read the full ClaimHawk case studyRelated service
AI Consulting
Not sure if you need a custom build or if an existing tool will work? Start with a consulting engagement. I'll assess your workflows and tell you the honest answer.
Get started
Book a discovery call
Tell me what your team does manually that you think a machine should handle. I'll tell you whether custom tooling is the right move and what it would take to build.
You know the workflow that's wasting your team's time. Tell me about it — I'll tell you what a custom AI tool would look like and what it costs.
Book a discovery call