Know exactly where AI pays off in your business. In 14 days.

A fixed-fee audit that ranks every AI opportunity by money and risk. Then we train your team and build the winners, with a partner who stays after launch.

See if you qualify See packages

Audit slots are limited each month. Five questions, a reply within one business day.

HealthcareConsumer goodsManufacturingRegulated financialPrivate equity portfoliosGrowing small businessYour industry

Pick your starting point.

Every package is a fixed fee, quoted to your team size and number of users, and scoped in writing before work starts. Teams that want a real answer, not just a workshop, start with the audit.

Team Workshop

Your people get confident with Claude on their own work.

Fixed feeQuoted to your team size and number of users

One live cohort session.

Half-day hands-on workshop
Breakouts on your real company problems
Rollout guidance for your Team or Enterprise plan
Reference guide your team keeps
Audit scorecard of where AI pays off
Working prototype on your data
Data and security read
Build quote and roadmap

Best value

Audit + Workshop

The full answer: where AI pays off, proven on your own data.

Fixed feeQuoted to your business size and scope

Two weeks. One business unit or brand.

Workshop included. The Team Workshop is part of this package at no extra cost.

On-site or remote shadowing of real workflows
Ranked scorecard: value, effort, data readiness, risk
Working prototype on your own data
Data and security read, with access rules set up front
Honest read on your current AI tools and where Claude fits
Build quote and a roadmap in payback order
Audit fee credited toward any build you start with us

Not sure which fits? Answer five questions and we'll recommend one. Take the questionnaire

After the audit: build, prove, launch, improve.

The audit tells you what to build. This is how it gets built and stays useful. Each stage earns the next, and you can stop at any point.

Build

We build the top audit winner inside your systems and your own cloud tenancy, on your real data.

You getA working solution your team can use on real work

Prove

Before go-live, we test it against real cases from your business, including the messy ones.

You getAn eval report: pass rate, failure types, and the rule that anything uncertain or high-risk goes to a person

Launch

We roll it out to named users and train them on their own work.

You getA one-page guide: how to use it, what it won't do, what it costs to run and what breaks it, plus an adoption metric we track

Improve

A monthly partnership sized by hours: extended training, office hours, tuning, and the next build.

You getOngoing access to your lead, with hours agreed each month

Typical first builds

Reconciliation exceptionsWeekly reporting dashboardCustomer service email triageDeduction recoveryMeeting prep packetsInternal knowledge agent

Each build is a fixed fee, quoted from the audit, with your audit fee credited. The monthly partnership is sized by the hours you need.

The fee works for you either way

Build with us and the audit fee is credited toward the build. Don't, and you keep the scorecard, the prototype and the plan.

No open-ended hours

Scope and hours are capped in writing before work starts. Anything bigger becomes its own fixed-fee project.

NDA before your data moves

We sign first, set data-boundary rules, and respect your existing access controls.

Shadow, score, show, ship.

No month-long discovery. You see real output in week one. This is how the two-week audit runs.

Shadow

We watch the work happen. Spreadsheets, inboxes, copy-paste, the one person who knows where everything is.

Days 1 to 4

Score

Every opportunity is rated on value, effort, data readiness and risk. Some get a clear no. That is the point.

Days 5 to 8

Show

We build a prototype on your own data so the decision rests on something real, not a slide.

Days 9 to 12

Ship

You get the ranked roadmap, a build quote and a training plan. Move forward with us or take it elsewhere.

Days 13 and 14

Before day one

Setup and configuration are covered on a short kickoff call, so there is nothing to prepare. Here is what we will ask for.

A sponsor who can say yes
A 30-minute kickoff call
Time with the 3 to 5 people who do the work
One IT contact for plan setup, sign-in and data access, after the NDA

Who this is for, and who it isn't.

A good fit

You run a company or portfolio business in the $20M to $1B range
Your team loses hours to data scattered across systems
You want a partner accountable for results, not a slide deck
Someone with authority can say yes within a few weeks

Probably not a fit

You want the cheapest possible chatbot
You can't give us access to the people doing the work
You want a one-off build with no plan to adopt it
You're curious but have no budget set aside

Many systems. One governed answer.

A representative engagement: data unification and an internal knowledge agent.

Operations teams spend hours a day cross-referencing data spread across disparate software, databases and documents. Every answer exists somewhere. Nobody can say where, and the person who could is on vacation.

We unify the fragments into one governed, vector-indexed knowledge base and put a retrieval-augmented agent on top, inside Slack or Teams. Data-boundary rules are set during the audit, so the same build holds up in HIPAA and FINRA settings as well as in a consumer brand.

Not every problem needs AI. The audit tells you which one you have. Outcome measures and references are shared on request, with client permission.

CRM and sales records

ERP and finance systems

Docs, wikis and drives

Tickets and shared inboxes

pipelines, cleaning, access rules

Governed, vector-indexed knowledge base

retrieval-augmented agent

Answers in Slack or Teams, cited to source

40+combined years of enterprise automation and data integration across the team

5+sectors worked: health, CPG, manufacturing, financial, small business

1accountable lead on every engagement

Day 1working from your real data, not demos

A team that sits inside your workflow.

Ridgeview Labs is led by Chad Carmeans, an integration engineer with 15 years inside large health systems (HL7, FHIR, APIs, data) who now applies that discipline to AI. Behind him is a bench of specialists for data and back-end work, with more than 40 years of combined enterprise automation and data integration experience. You get one accountable lead and a team behind him. We are Claude-first, and we say so plainly. Everyone we work with is a partner.

Our rule on every project: deliver as much value as quickly and safely as possible.

Questions we get

What does this cost?

It depends on the size of your business, the number of users and the scope. Every package is a fixed fee, quoted after a short call and agreed in writing before work starts. Builds beyond the audit are quoted the same way, and the audit fee is credited toward them. The monthly partnership is sized by the hours you need.

What happens after the audit?

We build the top opportunity, test it against real cases, launch it with your team, and keep improving it through a monthly partnership. Each stage is agreed separately, so you can stop at any point.

Why is the audit more than the workshop?

The workshop teaches your people. The audit tells you what to build, proves it on your data, and gives you a plan with numbers. It takes two weeks of shadowing, analysis and prototyping, and the workshop is included.

Do you work with Claude only? We use ChatGPT or Copilot.

We are Claude-first. Our training and builds run on Claude, on Team and Enterprise plans, because it is what we know best and have shipped. If your company runs on ChatGPT or Copilot, we will tell you plainly where that fits and where Claude does better. For deep work on another platform, we bring in a specialist partner instead of pretending to be experts in it.

What do you need from our IT team?

One contact for plan setup, sign-in (SSO) and data access, after an NDA is signed. We cover the details on a short kickoff call, so your IT team gets a clear list and not a surprise.

Do you need access to our data?

Only what the audit needs, and only after an NDA is signed. We set data-boundary rules first and respect your existing access controls.

What if the audit says we shouldn't build anything?

Then that is what we tell you, and you have saved yourself a bad project. The scorecard, prototype and plan are still yours.

Who actually does the work?

One accountable lead owns the engagement. Specialists and AI agents handle build work under that lead, so you get speed without losing a single point of responsibility.