If your team is searching old docs, routing leads by hand, copying data between tools, or answering the same support questions every week, I can turn one painful workflow into a working system your team can use, inspect, and measure.
Best fit: a workflow that burns 10+ hours a week, costs at least $15k a year in time, or slows down revenue, support, onboarding, or reporting.
Start here if manual search, routing, reporting, CRM cleanup, support triage, or admin work is costing real time. I will review the fit and send back the clearest next step.
The best AI automation projects are not vague chatbots. They connect messy inputs, rules, retrieval, review paths, and the tools your team already uses.
This is the pattern behind docs search, support triage, lead routing, invoice intake, and CRM cleanup.
The best first build is rarely a giant AI transformation. It is one recurring workflow where your team already knows the pain and the data already exists.
Teams search PDFs, contracts, support docs, invoices, job files, or internal notes before they can answer basic operational questions.
Inbound leads sit in inboxes, forms, CRMs, or spreadsheets while someone manually qualifies, tags, assigns, and drafts next steps.
People copy information between email, spreadsheets, billing tools, CRMs, and dashboards because the systems do not talk cleanly.
Ask Stripe documentation a technical question and see the retrieval pattern behind internal docs search, support triage, and implementation copilots.
Try the demoA small workflow can quietly burn thousands of dollars a year when senior people are searching, copying, routing, and rechecking work by hand. This starts at a realistic operator scenario; adjust it down if your pain is smaller.
Time spent searching, copying, routing, or rechecking
Includes a simple 1.3x labor burden estimate
Send the workflow that creates the drag. I will tell you whether it is worth automating, whether a simpler fix is better, and what a fixed-scope build would require.
I choose the right search pattern for the workflow: pgvector, hosted vector search, keyword fallback, metadata filters, or hybrid retrieval when accuracy matters more than novelty.
Builds connect to the tools your team already uses: Slack, email, CRM, docs, billing, databases, internal admin panels, or support queues.
The system logs what happened, shows what needs review, and avoids silent failures. When AI is unsure, it routes the work to a human instead of guessing.
For RAG and search systems, answers include citations back to the source material so your team can verify the result before acting on it.
Built on the tools your team already uses.
A simple path from messy manual work to a production AI system your team can actually use.
We identify the one manual loop where AI can save real time: lead routing, document lookup, support triage, CRM cleanup, invoice work, or internal reporting.
You get a plain-English workflow map, feasibility read, technical plan, and fixed-price build quote within 72 hours.
Build and deploy the full production system in 2 to 4 weeks. You own the code and data infrastructure.
One painful workflow, one clear system, one measurable improvement.
"Stop passing permit PDFs around in email. Move to a live job record where permit requirements, status, and documents are all attached to the work order."
Start where the pain is obvious: search, routing, triage, reporting, and admin loops that already cost time every week.
Search PDFs, docs, support content, product specs, or API references and return answers with citations your team can verify.
Classify inbound requests, enrich context, update the CRM or helpdesk, and alert the right person before the lead or ticket goes cold.
Extract, validate, sync, and report data between email, CRM, billing, spreadsheets, dashboards, and internal tools with clear review paths.
Custom code gives you version control, logs, tests, and explicit failure handling when the workflow matters enough to stop duct-taping it together.
Most first builds land in a $4,000 to $8,000 sprint once the workflow is clear. You know what is being built before the meter starts running.
You work directly with the person mapping the workflow, building the system, and handing over maintainable source code.
Send the manual workflow that is costing time. I will tell you whether it is a good AI automation candidate and what the practical next step should be.
REVIEW A WORKFLOW