Manual data extraction. Repetitive workflows. Scattered data nobody can act on. I build AI systems that eliminate the bottleneck and give your team their time back.
These aren't technology problems. They're bottlenecks disguised as normal — and they're costing you more than you think.
Your team spends hours copying data from PDFs, emails, and spreadsheets into your systems. It's tedious, error-prone, and nobody's core job.
The same multi-step process, run manually, every single day. One person knows how it works. If they're sick, everything stops.
Your data lives in five different places, none of them talk to each other, and turning it into a decision takes a full day of prep.
Not tools. Not automations. Intelligent systems — built end-to-end, designed around your specific workflow, and deployed to run without babysitting.
Turn PDFs, documents, and unstructured inputs into clean, structured data — automatically. No more manual copy-paste. No more missed fields.
The 5-step process that takes your team 2 hours? Built once. Runs in 4 minutes. End-to-end, from input to output, without a human in the loop.
Fragmented data from five sources, unified into one live view. From raw inputs to actionable dashboards — without a data team.
Every project listed here ran in production. These are real outcomes, not estimates.
Replaced a 20-minute manual PDF review process with an AI pipeline that extracts, validates, and structures data in under 2 minutes — across hundreds of documents per day.
Consolidated a 6-step manual process — involving 3 team members, 4 tools, and 2 hours of daily work — into a single automated pipeline that runs on a schedule.
Unified data from 5 disconnected sources into a single real-time dashboard. Replaced a weekly 4-hour data consolidation exercise with a live view refreshed every 15 minutes.
A look at how an AI extraction pipeline is designed, built, and deployed end-to-end.
Any format — PDF, Word, Excel, scanned. The system normalises structure before processing.
AI identifies tables, field labels, relationships, and nested data — even across irregular layouts.
Every field is extracted, validated, and mapped to your target schema. No hallucinations, no guesswork.
Clean data pushed to Excel, JSON, your CRM, or your database — automatically, on every run.
From the people who ran these systems in production.
We were spending 3 hours every morning pulling data from client reports. Now it runs overnight and the structured output is waiting in our dashboard when we open our laptops. Game-changer.
I didn't think you could automate our onboarding workflow — it was too messy and had too many edge cases. EchoNerve built a system that handles 90% of it without touching it.
The dashboard pulls from our CRM, our billing tool, and our spreadsheets — and it's live. We used to spend Fridays preparing the Monday review. Now we just show up.
Each tool is a standalone version of a larger system. Try the demo — then tell me what you need built.
Upload a PDF and watch structured data come out the other side. Tables, fields, nested data — all handled.
Try the Demo →Describe your process in plain English. Get an automation architecture back — steps, logic, and tooling mapped out.
Try the Demo →Paste in messy, unstructured data. Get clean, consistent, schema-ready output back instantly.
Try the Demo →Beyond OCR — extract meaning, relationships, and context. Works on contracts, reports, invoices, and more.
Try the Demo →Adjust the inputs. Numbers update live — using real averages from deployed systems.
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EchoNerve is my practice — focused entirely on building AI systems that run in production. Not prototypes. Not POCs. Systems that your team uses every day and that you'd notice immediately if they stopped.
My background is in the intersection of AI, process design, and data engineering. I've built extraction pipelines for financial documents, automated operations workflows for SaaS teams, and live intelligence dashboards for businesses making daily decisions from scattered data.
I take on a small number of projects at a time. Every engagement gets my full attention — from scoping the system to deploying and handingoff the final product.
Most automation saves a click.
I build systems that eliminate the process.
No generic templates. Every system starts with understanding how your process actually works — edge cases and all — before a single line is written.
The systems I build handle errors, edge cases, and volume. They don't break at 3am on a Sunday when someone uploads an unusual file format.
Every system ships with documentation your team can use, clear operating instructions, and a handoff call. You own it. You run it.
How AI systems actually get built — the architecture decisions, the failure modes, and what most vendors won't tell you.
Demos always work. Production is different. The three architectural mistakes that cause extraction systems to break under real workloads.
Most workflow automations break because of edge cases nobody planned for. Here's how to design a pipeline that handles what you didn't think of.
A tool solves one problem once. A system solves a category of problems forever. The framing shift that changes how you invest in AI.
The best projects start with a simple description of what's broken. Tell me the process, the bottleneck, or the outcome you want — I'll tell you exactly what I can build.