We've had technology projects stall. What's different here?

The scale and the evidence. One workflow, a dated baseline, a plan your team helps shape and a go or no-go decision before anything is built. If the numbers don't justify building, we'll recommend you don't.

Will this replace people on our team?

That's not what we design for. The aim is capacity: helping the team you have handle more, faster, with fewer errors. People keep the judgment calls and the relationships.

How much of our team's time does this take?

Discovery is designed to keep your team's time small: a few interviews with the people who do the work, and one workflow owner to coordinate samples and introductions.

How do you handle confidential data?

In writing, before any build. We document what data the workflow touches, which vendors process it and how they're configured. Work runs in accounts you control wherever possible, access is limited to what the workflow needs, and how it's removed at handoff is agreed up front. Please don't include confidential information in an inquiry.

We're regulated. Can we use AI safely?

Often, with the right boundaries. We design so that licensed advice, binding commitments, pricing and customer communications stay with qualified people. Before work begins, we review your compliance and vendor-oversight requirements with you and say plainly which we can meet and which we can't. We flag regulatory and coverage questions; your counsel, compliance lead or insurer decides them.

Every engagement is scoped and priced in writing before any work begins. Implementation is priced from what Discovery finds, so you know the investment before you commit.

Do you build custom software?

When it's the right answer. Most fixes use tools you already own. When custom work is the better answer, we'll say so and scope it in writing.

AI Consulting, Automation & Implementation for Established Businesses

Find the work worth fixing. Fix it. Measure it.

FindMeNow.ai helps established businesses put AI and better-connected software to work where it pays off: one workflow at a time, with people in charge of the decisions that matter, and results measured against where you started.

Start with one workflow See an example map

Every engagement starts with a conversation, and nothing begins until scope and fees are agreed in writing.

One workflow at a time
Measured from a dated baseline
Named approvers

Workflow Discovery · example map

Illustrative example

New client inquiry, professional services firm

Steps 1 to 6 of 9

01Inquiry lands in a shared inboxSoftware
02Work out which partner it's forRemove
03Email back for missing detailsAI assist
04Copy details into the CRM and a spreadsheetSoftware
05Research the prospectAI assist
06Check for conflicts and fitPerson

Of 9 steps: AI assists 2, software handles 4, 1 disappears and 2 stay with people.

Open the full map

01 / Where the time goes

The work that quietly caps your growth

In most established businesses, the constraint isn't effort or ambition. It's the same details typed into three systems, requests that sit until someone has time, answers that live in one person's head, and reports rebuilt by hand every week. None of it shows up as a line item. It shows up as slower responses, avoidable errors and a team that can't take on more without hiring.

Re-keying
The same details entered into email, a spreadsheet and the system of record.
Waiting
Requests that sit in a shared inbox, then wait again for missing information.
Searching
Procedures, policies and product answers that depend on who you ask.
Assembling
Reports rebuilt by hand, so decisions run on last month's numbers.

AI can help with all four. Not on its own, and not everywhere. That's why we start by looking.

02 / Workflow Discovery, by example

Most of the opportunity isn't AI.

We take one workflow apart, step by step, and give every step one of four treatments: remove it, automate it with ordinary software, assist it with AI, or keep it with a person. The redesigned workflow is usually simpler than people expect, and AI is only one part of it.

Workflow Discovery · example map

Illustrative example

New client inquiry to first meeting

Example: professional services firm

03 / 09

Email back for missing details

Who: Assistant
Systems: Email
Today: Back-and-forthTwo or three rounds of back-and-forth
Treatment: AI assistDrafted, then approved
Redesigned: A reply asking only for what's missing is drafted in the firm's voice. The assistant approves it.
Why: Inquiries vary. A tailored draft saves time, and a person checks it before it goes.

Approved by: Assistant

Of 9 steps: AI assists 2, software handles 4, 1 disappears and 2 stay with people.

Stays with people: Conflict checks and the decision to take on a client.

What we'd measure: Time from inquiry to first meeting · Inquiries that never get a reply · Staff time per inquiry

Remove: the step disappears.
Software: rules and connections, no AI.
AI assist: AI reads, sorts or drafts, and a person checks.
Person: a named person decides.

Illustrative example. Steps are simplified; this is not a client workflow or result.

See what Workflow Discovery includes

03 / How we work

AI has to earn its place.

Start with the work, not a tool.
We begin with how a workflow actually runs today, then use the simplest fix that works: a better form, a rule, a connection between systems, or AI where it truly helps. Sometimes the answer is a feature you already pay for. Sometimes it's "not yet."
People stay accountable.
Every workflow we implement comes with a written "who approves what": what runs automatically within rules you set, what AI drafts for a person to approve, and what only a qualified person decides.
Measured from a dated baseline.
We record how the work performs before anything changes and measure the same things after launch. You see what improved, and what didn't.

04 / What we fix

Five places to start

Across industries, the strongest opportunities fall into the same five areas. Most engagements begin in one.

Five places to start
	Insurance agency	Premium retail	Professional services
01Respond to new business faster. Problem: Inquiries wait, follow-up depends on memory, and good prospects go quiet. What we do: Intake that captures the right details the first time, routing to the right person, drafted replies and follow-ups for approval, and a CRM that stays current without retyping. Stays with people: Advice, pricing and commitments.	Quote requests gathered completely before a producer picks them up.	Showroom and consultation follow-up that's timely and on-brand.	From inquiry to booked meeting without the back-and-forth.
02Clear routine requests and paperwork. Problem: Skilled people spend the day re-keying, chasing missing details and filing. What we do: Structured requests, document reading with field-by-field review, and connections that move confirmed information between systems. Stays with people: Judgment calls and anything submitted in your name.	Policy change, certificate and ID card requests prepared for quick review.	Order problems organized with photos, order details and next steps.	Client documents collected, checked for completeness and filed.
03Put company knowledge to work. Problem: The answers exist in procedures, policies and past emails, but finding them depends on who you ask. What we do: An assistant that answers from your approved sources, shows where each answer came from, and says when it doesn't know. Stays with people: Owners decide what's approved and keep it current.	Agency procedures and carrier guidelines, searchable with sources.	Product, care and policy answers that match across stores and channels.	Procedures and past work a new hire can actually use.
04Use AI safely as a team. Problem: People already use AI on personal accounts, with no policy and no shared standard. What we do: Company accounts configured for your data settings, a plain-language AI policy, approved uses by role and practical training. Stays with people: Leadership sets the rules. Managers own adoption.	A written AI policy and approved uses that fit your data obligations.	Store and support teams moved from personal tools to managed accounts.	Training on the handful of tasks each role does most.
05See the operation clearly. Problem: Reports are assembled by hand, so decisions run on stale numbers. What we do: Agreed metric definitions, automatic data refresh and a dashboard that ties each number to an owner and a next action. Stays with people: Interpreting the numbers and deciding what to do.	Renewals, service backlog and new business in one current view.	Store, service and delivery measures reconciled without spreadsheet work.	Pipeline, capacity and client status, refreshed automatically.

Respond to new business faster.

Problem:: Inquiries wait, follow-up depends on memory, and good prospects go quiet.
What we do:: Intake that captures the right details the first time, routing to the right person, drafted replies and follow-ups for approval, and a CRM that stays current without retyping.
Stays with people:: Advice, pricing and commitments.

Insurance agency: Quote requests gathered completely before a producer picks them up.
Premium retail: Showroom and consultation follow-up that's timely and on-brand.
Professional services: From inquiry to booked meeting without the back-and-forth.

Clear routine requests and paperwork.

Problem:: Skilled people spend the day re-keying, chasing missing details and filing.
What we do:: Structured requests, document reading with field-by-field review, and connections that move confirmed information between systems.
Stays with people:: Judgment calls and anything submitted in your name.

Insurance agency: Policy change, certificate and ID card requests prepared for quick review.
Premium retail: Order problems organized with photos, order details and next steps.
Professional services: Client documents collected, checked for completeness and filed.

Put company knowledge to work.

Problem:: The answers exist in procedures, policies and past emails, but finding them depends on who you ask.
What we do:: An assistant that answers from your approved sources, shows where each answer came from, and says when it doesn't know.
Stays with people:: Owners decide what's approved and keep it current.

Insurance agency: Agency procedures and carrier guidelines, searchable with sources.
Premium retail: Product, care and policy answers that match across stores and channels.
Professional services: Procedures and past work a new hire can actually use.

Use AI safely as a team.

Problem:: People already use AI on personal accounts, with no policy and no shared standard.
What we do:: Company accounts configured for your data settings, a plain-language AI policy, approved uses by role and practical training.
Stays with people:: Leadership sets the rules. Managers own adoption.

Insurance agency: A written AI policy and approved uses that fit your data obligations.
Premium retail: Store and support teams moved from personal tools to managed accounts.
Professional services: Training on the handful of tasks each role does most.

See the operation clearly.

Problem:: Reports are assembled by hand, so decisions run on stale numbers.
What we do:: Agreed metric definitions, automatic data refresh and a dashboard that ties each number to an owner and a next action.
Stays with people:: Interpreting the numbers and deciding what to do.

Insurance agency: Renewals, service backlog and new business in one current view.
Premium retail: Store, service and delivery measures reconciled without spreadsheet work.
Professional services: Pipeline, capacity and client status, refreshed automatically.

Most fixes use software you already own. When a custom tool is the better answer, we'll say so and scope it in writing. What's possible depends on your systems, their vendors and the access available, and Discovery confirms it before anything is promised.

Prefer to start smaller? Executive AI Setup, Team AI Setup and marketing dashboards are scoped starting points.

Explore smaller starting points

05 / Control

Built so you can check the work.

Trust comes from how a workflow is designed, not from promises. Each implementation proposal includes a written approval ladder and a plain-language data review.

Who approves whatIllustrative example

Tier 1
Runs within rules
Examples: acknowledgments, routing, reminders and status updates from approved templates.
Oversight: a person approves the rule or template once and reviews samples.
Tier 2
Drafted, then approved
Examples: replies outside templates, file notes, document data before it's saved.
Oversight: a named person approves each item.
Tier 3
Decided by a qualified person
Examples: advice, coverage and contract changes, pricing, refunds above a set limit, exceptions.
Oversight: AI may prepare information. It never decides.

Your accounts, your data
Wherever possible, what we build runs in accounts you own. Ownership and handoff terms are agreed in writing before work begins.
Only the access a workflow needs
Access is granted through your administrator and limited to the workflow. At handoff we ask your administrator to remove it and confirm when it's gone. Never send passwords by email.
Sources shown
We design AI steps to show the sources they used, so a reviewer can check them quickly.
Tested and documented
Changes are tested before launch and documented for your team, with a plan to turn each one off or roll it back where your systems allow.
A plain-language data review
Before any build, we document what data the workflow touches, which vendors process it and how their settings are configured.
Built to run without us
You get an operating and recovery guide, and we design workflows to run on your own accounts without ongoing help from us. Anything that depends on us or another provider is named in the proposal.

How we handle data and approvals

06 / How to start

Start small. Prove it. Then expand.

01
Conversation
A conversation about one workflow or one question.
02
Find: Workflow Discovery
A defined engagement on one workflow, scoped and priced in writing before it starts: the map, a dated baseline, a treatment for every step, a feasibility test on real cases, your options and a clear recommendation.
03
Fix: Implementation
If Discovery shows the fix is worth doing, we agree the scope in writing, including anything that depends on your systems, access or vendors. Then we build or configure it, test it against real cases with your team and launch it with approvals in place.
04
Measure: Results and next steps
We measure the same things again after launch. Then you decide: refine it, take on the next workflow, or stop.

Measurement plan · example format

Measure	How it's measured	Baseline	After launch
Measure: Time from request to completion	How it's measured:From timestamps in your systems	Recorded during Discovery	Re-measured after launch
Measure: Touches per request	How it's measured:From a sample of real cases	Recorded during Discovery	Re-measured after launch
Measure: Rework and corrections	How it's measured:From review notes and edits	Recorded during Discovery	Re-measured after launch
Measure: Staff time	How it's measured:From short time studies with your team	Recorded during Discovery	Re-measured after launch

Baseline:: Recorded during Discovery
After launch:: Re-measured after launch

Your numbers, measured, not estimated.

07 / Proof, not promises

We run AI in production ourselves.

FindMeNow began with AI Visibility, a system we designed, built and operate. It asks AI assistants the questions a business's customers ask, records each answer with its sources and date, checks whether the business was named, and assembles a private report. Running it means solving the same problems a business workflow faces: queued work, spending limits, provider failures that must be labeled rather than hidden, private access and a person reviewing the results.

See a sample report

08 / Accountability

One accountable lead, from first conversation to handoff.

FindMeNow is founder-led by design. JJ Resnick scopes every engagement, leads the work and stays accountable for it, so nothing gets lost between the person who scoped the project and the work itself. When a project needs a specialist, you'll know who and why before it's in a proposal.

JJ has spent more than 20 years building and marketing businesses online, in ecommerce and direct-to-consumer. JJ is also a partner in Agavia, a tequila and mezcal tasting room in San José del Cabo, and created FindMeNow's AI Visibility system.

About JJ and FindMeNow.ai

09 / Questions

Questions leaders ask

You may not need to for every workflow. Part of Discovery is checking what your current tools already do, or will soon, and whether that's enough. Often the gap isn't a missing feature. It's configuration, data quality and the steps around the tool. We'll tell you which.

Also from FindMeNow: AI Visibility shows what AI assistants tell customers about your business.

Explore AI Visibility

Get started

Bring one workflow. Leave with a clearer picture.

Tell us about a workflow that takes too much time, or a question about where AI fits. JJ reads every inquiry and replies directly.

Start with one workflow See what Workflow Discovery includes

Please don't include passwords or confidential customer information.

Find the work worth fixing. Fix it. Measure it.

The work that quietly caps your growth

Re-keying

Waiting

Searching

Assembling

Most of the opportunity isn't AI.

AI has to earn its place.

Start with the work, not a tool.

People stay accountable.

Measured from a dated baseline.

Five places to start

Respond to new business faster.

Clear routine requests and paperwork.

Put company knowledge to work.

Use AI safely as a team.

See the operation clearly.

Built so you can check the work.

Your accounts, your data

Only the access a workflow needs

Sources shown

Tested and documented

A plain-language data review

Built to run without us

Start small. Prove it. Then expand.

Conversation

Find: Workflow Discovery

Fix: Implementation

Measure: Results and next steps