Cookies · Your choice

Analytics cookies, only if you say so

This site uses Google Analytics to count visits and see which pages get read. Those cookies stay off until you allow them. Everything the site needs to work runs without them. Cookie Policy.

This site uses Google Analytics to count visits. You can opt out at any time on Your Privacy Choices. Cookie Policy · Your Privacy Choices

Fincel DesignRev. 2026

§ Field dossier

Kevin FincelI put AI to work in your business.

Forward Deployed AI Engineer · Founder, Geol.ai · Jacksonville Beach → On-site → Remote

I work with your team to understand where the work gets stuck, then build AI into the systems you already use. That might mean helping staff work through quote requests, checking a product catalog, or connecting information that lives in different tools. I handle the build and deployment, and help your team put it to use.

  • Business automation
  • Connected systems
  • AI tools for your team
Kevin Fincel at his desk, about to speak
The film · 2 min 46 sFILM-01
Read the transcript
I think the traditional AI consulting model is backwards. Companies don’t need another person sitting outside the organization telling them what AI might someday do. They need somebody who can get inside the business, understand how it actually operates, find the opportunities, and then build the damn thing. That’s the role I’m building Fincel Design around. I’m Kevin Fincel, and I work as a Forward Deployed AI Engineer. For a long time, Fincel Design was how I helped companies build better websites, better marketing systems, and better digital experiences. But over the last couple of years, something changed. AI completely changed what I’m able to build, how quickly I can build it, and where I believe I can create the most value for a company. So Fincel Design is changing too. I’m not interested in being another AI consultant who talks once a month on a Zoom Call, hands you a strategy deck, talks about what’s possible, and then fades away. I want to work inside the problem. I want to understand how your organization actually works, your people, your data, your software, your workflows, the repetitive work, the disconnected systems, and the bottlenecks that are holding your team back. Then we figure out where AI can create real leverage. And then I build it. That could mean AI agents. Internal automation. MCPs. RAG systems. Data integrations. Custom software. New AI-powered products. Or completely rethinking a workflow that’s been done the same way in your organization for decades. The technology matters, but the technology isn’t really the point. The point is deploying something that actually works inside your business. Something your team uses. Something that saves time, creates capacity, improves decisions, generates revenue, or gives the organization a capability it simply didn’t have before. And in a lot of ways, this isn’t a complete reinvention for me. It’s the next evolution of what I’ve been doing for years, understanding businesses, understanding technology, and figuring out how to connect the two. The difference now is that the tools have become dramatically more powerful. And I think the opportunity for companies that learn how to deploy them effectively is enormous. That’s what the next version of Fincel Design is about. Don’t just talk about AI. Deploy it.
§ 01

What makes this work

I want to work
inside the problem.

Before I build anything, I need to understand how the work gets done. I spend time with the people doing it, trace the information they rely on, and find where the process gets stuck. Then I work out what is worth building.

As a Forward Deployed AI Engineer, I work inside your business to understand the workflow, build AI into your existing systems, and help your team use it. I handle the data connections and access rules, and stay involved through deployment and adoption.

I build AI agents, retrieval systems that find relevant information, and integrations with ERP, CRM, analytics and legacy software. I also build MCP servers, the connections that let AI use those tools. The work includes testing answers, access controls and human approval for sensitive changes.

We decide what the software can change on its own and what needs your team's approval. Then we test it. AI will get things wrong, and catching those mistakes is part of the work.

I've been responsible for getting business systems into daily use for more than eighteen years. The tools have changed. I'm still accountable for whether the thing works.

Building web and business systems
18+ yrs
Building web and business systems
Sales → delivery → P&L
3× founder
Sales → delivery → P&L
From the first call to daily use
Hands-on
From the first call to daily use
§ 02

Working with me

Start with the AI Deployment Sprint: two to three weeks of fixed-scope work. We choose a workflow and check its data and access requirements. You get a system map, risks, build plan and ROI estimate. Use the contact form to discuss scope and pricing.

Phase 1 · Start here

AI Deployment Sprint

  • Fixed scope
  • 2–3 weeks

The sprint gives you a clear decision about what to build and why. I spend the first two or three days at your business, watching the work and talking with your team. Over the rest of the two-to-three-week engagement, I check the data and access requirements, identify the risks, and put together the build plan and ROI estimate. We agree on how to measure success before the build starts. The plan is yours to use, whether I build it or someone else does.

Phase 2

Proof of Value → Production

  • Build and test
  • Ready for daily use
  • Scoped per engagement

The prototype and deployment are a separately scoped build stage. I build the workflow we chose in the sprint and test it against your data. Getting it into production also means sorting out access, logging and the steps that need human approval. Most of this happens from my office, with a visit for training if that helps your team. We keep working until your team can run it.

Ongoing

Fractional AI Lead

  • Monthly
  • Part-time technical leadership

For teams that need an AI lead but aren't ready to hire one full time. I help make architecture and vendor decisions, review the work, and get the team comfortable running it. I can also build when you need another pair of hands.

An engagement usually begins with two or three days at your business so I can see how the work gets done. I build and deploy from my office in Jacksonville Beach, Florida. We plan return visits for training with your company. My clients are mainly in the United States and Canada.

I won't sell you an AI build if the problem needs a simpler fix.

§ 03

Selected work

Here's some of the work I've built, from internal tools teams use every day to catalog and system integrations. Client and employer names are withheld. I can walk you through the work and discuss references in a conversation.

Current · Founder

Live product

Founder, Geol.ai

I founded and build Geol.ai, a product that tracks how AI search tools cite and recommend brands. It monitors ChatGPT, Perplexity, Claude, Gemini, Copilot and Grok, then generates structured content to help improve that visibility. It's a running product, and a lot of my work on retrieval comes from building it.

geol.ai ↗Technical briefing: “AI search engines vs. Google” ↗

Live

Case 01

A B2B marketing agency serving industrial manufacturers

Connecting AI to the tools an agency uses every day

I connected the team's AI tools to the software they use for ads, reporting and calls. Staff sign in with their own accounts, and the ad connection can't change live spending.

84 TOOLS · 5 SELF-HOSTED SERVERS

  • MCP / FastMCP
  • Cloud Run
  • OAuth 2.1 + DCR
  • Firestore + Fernet
  • Secret Manager
  • Python
Shipped

Case 02

The same agency; internal operations platform

Replacing a 12-tab spreadsheet with a shared operations app

I replaced a 12-tab trade-show spreadsheet with an app the team uses daily. Staff can update it directly or ask an AI assistant to do it. Every change is recorded.

92 MCP TOOLS · HAND-BUILT OAUTH 2.1

  • Next.js 15
  • React 19
  • Supabase Postgres
  • MCP
  • OAuth 2.1
  • RLS
  • Vercel
  • Audit logging
Shipped

Case 03

A multi-brand industrial services group

Auditing 2,014 domains for tracking and consent problems

After years of acquisitions, the company didn't know which websites were still running. I checked 2,014 domains and identified where visitor tracking needed consent controls.

2,014 DOMAINS PROBED · 27 LIVE · TRIAGED

  • HTTP/DNS probing
  • Headless-browser verification
  • GDPR / CPRA
  • Consent gating
  • Event-driven JS
  • Severity triage
In field

Case 04

A multi-brand industrial electrical-equipment group

Connecting a 59,886-item inventory catalog to a new storefront

I built the connection between the company's inventory system and its new website. Nearly 60,000 items sync in 5.4 minutes. The backend is verified; the website is still being built.

5.4 MIN FULL SYNC · 59,886 ITEMS · 100% HASH-STABLE

  • Next.js
  • TypeScript
  • Hono API
  • PostgreSQL + Drizzle
  • NetSuite (OAuth2 M2M, ES256)
  • Azure Container Apps
  • GitHub OIDC
  • OpenAPI 3.1
  • MCP
In field

Case 05

An industrial safety-equipment distributor

A 916-product catalog review the catalog owner could run

I built an AI-assisted check of 916 products against a 250-page guide. The employee responsible for the catalog ran the full review herself, with three checkpoints together.

916 PRODUCTS · OPERATOR COMPLETED THE REVIEW

  • Multi-agent orchestration
  • Adversarial verification
  • PDF extraction
  • WooCommerce
  • Data QA
  • Human-in-the-loop
In field

Case-study figures checked against source repositories and project records in August 2026.

§ 04

From the first call to daily use

The details change with the company. Here's how I usually work, and what you keep at each stage.

  1. 01

    Understand the work

    I spend two or three days at your business, talking to the people doing the work and tracing the systems behind it.

    You keep → A system map showing where the data lives and who can access it.

  2. 02

    Try it on your data

    In the separately scoped build phase, we try one workflow on your data before committing to a larger build.

    You keep → A working prototype and a set of tests for its answers.

  3. 03

    Put it into use

    I set up access, approvals and monitoring so the team can use it safely and you can see what it costs.

    You keep → Instructions for running it and handling problems.

  4. 04

    Help the team use it

    I watch how people use it, fix what gets in their way and train the team, on site if that helps.

    You keep → Usage and outcome measurements we can compare with where we started.

  • D-01 · Build on what you already run. Replacing a working system needs a good reason.
  • D-02 · People approve the changes that are hard to undo. We agree on those limits before an agent gets access.
  • D-03 · Trust is earned in production. Test the answers and keep a record of what happened.
§ 05

Ask Kevin

AI answers based on my published work · You can check the sources

Ask KevinAI assistant

Ask Kevin · AI

Ask about Kevin's projects, how he works, or where an engagement starts. The answers use his published work and link to the source.

Pressing Ask carries your question to the Ask Kevin page in this tab. Nothing is sent to a model until you ask there.

Standard · May use a hosted model · What this mode does

Your question and matching passage IDs go to this site's server, then to a hosted AI model. OpenRouter requests are routed only to providers that do not collect the request for their own use, so it is not used to train a model. Prompt logging is off on Kevin's OpenRouter account, so OpenRouter keeps the routing record and not your words. How long the provider that answers keeps it is set by their policy. How this answer was produced shows which model and provider answered. Please leave out confidential material.

The first question downloads about 58 MB of model and runtime files from this site. Your browser caches them for later questions.

Recorded example · 2026-09-14One question · 3 sources, word for word · No hosted model

Specimen · Recorded run · 2026-09-14 · Corpus 24292ff9 · No generative model · Matching source passages, word for word

We run Salesforce, three legacy databases, and our salespeople qualify RFQs by hand. What could Kevin build for us?

EvidencedSimilarity 0.659 · Floor 0.55

No generative model · Matching source passages, word for word

  1. Kevin Fincel · What I buildSimilarity 0.659
    I build AI agents, retrieval systems that find relevant information, and integrations with ERP, CRM, analytics and legacy software. I also build MCP servers, the connections that let AI use those tools. The work includes testing answers, access controls and human approval for sensitive changes.
  2. Kevin Fincel · Case 06 · AI-assisted ad changes with approval before every change · ProblemSimilarity 0.627
    The team manages about 18 industrial-sector ad accounts. Agents can help with audits and campaign builds, but API changes affect live client spend. I needed a review process that made each change traceable and required a person to approve it before execution.
  3. Kevin Fincel · ThesisSimilarity 0.621
    I want to work inside the problem. Before I build anything, I need to understand how the work gets done. I spend time with the people doing it, trace the information they rely on, and find where the process gets stuck. Then I work out what is worth building. As a Forward Deployed AI Engineer, I work inside your business to understand the workflow, build AI into your existing systems, and help your team use it. I handle the data connections and access rules, and stay involved through deployment and adoption. I build AI agents, retrieval systems that find relevant information, and integrations with ERP, CRM, analytics and legacy software. I also build MCP servers, the connections that let AI use those tools. The work includes testing answers, access controls and human approval for sensitive changes. We decide what the software can change on its own and what needs your team's approval. Then we test it. AI will get things wrong, and catching those mistakes is part of the work. I've been responsible for getting business systems into daily use for more than eighteen years. The tools have changed. I'm still accountable for whether the thing works.

This example was recorded at build time using the same model as the browser. It uses source passages word for word; no hosted model wrote the answer.

§ 06

Hiring for an FDE role?

If you're hiring a Forward Deployed Engineer, compare your role with the work I've done. The reader below links requirements to my case studies and flags where the experience doesn't match.

Fit readRuns in your browser

Compare this role with Kevin's work

Paste a job description to compare it with Kevin's work. The text stays in your browser.

0 / 40,000 chars · Your job description never leaves this tab
Or try a sample
Agent-ready

If you're using an AI agent to research me, /llms.txt gives it an overview, /resume.json and /resume.txt provide my background, and /AGENTS.md has agent instructions. It can read /api/hire and send an introduction through /api/contact. The site is the demo.

Opens the file here so you can see what an agent reads.

§ 08

Field notes

Notes on systems I've built and decisions I had to make along the way.

§ 09

About

Portrait of Kevin Fincel
K. Fincel · Jacksonville Beach, FL

I've been building for businesses since 2008.

I'm Kevin Fincel, a Forward Deployed AI Engineer and three-time founder in Jacksonville Beach, Florida. For more than eighteen years, I've worked with businesses to understand how they operate and build the software they need. I'm used to being the person responsible when something breaks.

I lead AI infrastructure at a B2B marketing agency serving industrial manufacturers. I built its self-hosted MCP servers and the agent tools the team uses daily. I also founded Geol.ai, which measures how AI engines cite and recommend brands. Before that, my work covered full-stack web development, enterprise cloud and ERP integrations, often working directly with company leadership.

I've run workloads on Google Cloud (GCP) for five years and used Google Tag Manager (GTM) for six, including server-side tagging and consent-aware deployments. I've had Node.js (Node) services in production for two years.

Fincel Design, LLC is the company I founded in 2008. Today, my focus is building AI into the way companies work.

Experience details

  • Web and systems delivery: at least 18 years as of 2026-09 (attested 2026-09-02). Covers: web and systems delivery, web systems, full-stack development, full-stack product engineering.
  • TypeScript: at least 2 years as of 2026-09 (attested 2026-09-03). Covers: typescript.
  • Node.js: at least 2 years as of 2026-09 (attested 2026-09-04). Covers: node.js, node.
  • SQL: at least 8 years as of 2026-09 (attested 2026-09-03). Covers: sql.
  • Python: at least 6 years as of 2026-09 (attested 2026-09-03). Covers: python.
  • PHP: at least 9 years as of 2026-09 (attested 2026-09-03). Covers: php.
  • WordPress: at least 10 years as of 2026-09 (attested 2026-09-03). Covers: wordpress.
  • Docker: at least 2 years as of 2026-09 (attested 2026-09-03). Covers: docker.
  • AWS: at least 5 years as of 2026-09 (attested 2026-09-03). Covers: aws.
  • Google Cloud: at least 5 years as of 2026-09 (attested 2026-09-04). Covers: google cloud, gcp.
  • HubSpot: at least 3 years as of 2026-09 (attested 2026-09-03). Covers: hubspot.
  • Pardot: at least 4 years as of 2026-09 (attested 2026-09-03). Covers: pardot.
  • Google Tag Manager: at least 6 years as of 2026-09 (attested 2026-09-04). Covers: google tag manager, gtm.
  • CI/CD: at least 5 years as of 2026-09 (attested 2026-09-03). Covers: ci/cd.
  • Location: Jacksonville Beach, FL, US; remote available (attested 2026-09-03).
  • Work authorization: United States (attested 2026-09-03).
  • Work authorization: Canada (attested 2026-09-03).
  • Founder · Fincel Design, LLC · 2008present
  • Founder · Geol.ai · 2025-08present
  • AI infrastructure lead · B2B marketing agency (name withheld by policy) · 2018-10present

Confirmed by Kevin · 2026-09-04 · Kevin Fincel

These are the profile facts I've confirmed for Ask Kevin. It quotes them directly and does not infer additional profile facts.

§ Cookies

Choose what this site may keep in your browser. Details for every item are in the Cookie Policy. You can change this at any time from the bottom of any page. Cookie Policy.