Services What we do

Four services. One standard: it has to pay back.

Q: Do we need clean data or a data team first?

No. Most mid-market companies have neither, and the best early opportunities often work with messy documents and existing systems.

Each service produces a measurable business outcome, not a deliverable. Most clients start with Strategy and move into Build; some arrive with a known problem and go straight to Automation or Solutions.

01 Strategy & Transformation 02 Intelligent Automation 03 Custom AI Solutions 04 Fractional AI Leadership

AI Strategy & Transformation

Know exactly where AI will create value in your business — and where it won’t — before you commit capital.

Typical entry point

AI Opportunity Assessment

A fixed-scope, 2–4 week engagement that ends in a ranked opportunity portfolio, payback estimates and a recommended build sequence. Priced as a discovery project; scoped on the strategy call.

Most AI strategies fail in the same way: they inventory possibilities instead of ranking them. We approach your business the way an operating partner would — margin structure, labor intensity, cycle times, data assets, competitive pressure — and translate that into a short list of opportunities with explicit financial hypotheses.

What you get

Operational and data landscape map
Ranked opportunity portfolio (impact × feasibility × risk)
ROI model per opportunity with assumptions exposed
Build / buy / wait recommendations
12–18 month roadmap sequenced for early payback
Executive briefing and board-ready materials

Business outcomes

Capital directed to the few opportunities that clear a return threshold
Leadership alignment on priorities and sequence
Vendor and tooling decisions made with discipline
A defensible answer to “what is our AI strategy?”

Also offered

Ongoing executive advisory; AI diligence for acquisitions; vendor evaluation and negotiation support.

Intelligent Automation

Remove manual work from the processes that cost you the most — with AI agents and integrations that run inside your existing systems.

Typical engagement

Fixed-scope workstreams, 6–12 weeks each

Each workstream targets one process with a baseline, a payback target and an owner on your side. Implementation engagements are scoped from the assessment or from a defined problem you bring to us.

The automation opportunities worth pursuing are rarely the glamorous ones. They are intake queues, document handling, exception processing, reconciliation, scheduling and the hundreds of small decisions that currently route through a person because the inputs are messy. Modern language models handle that mess well — if they are engineered with guardrails, observability and a human in the loop where judgment matters.

What we build

Document and email processing (extraction, classification, routing)
AI agents for intake, triage, quoting and follow-up
Workflow orchestration across ERP, CRM and line-of-business systems
Exception handling with human review queues
Monitoring, audit trails and quality controls

Business outcomes

Lower cost-to-serve on high-volume processes
Shorter cycle times from request to resolution
Reduced error and rework rates
Capacity recovered without adding headcount
Measured against the baseline captured before build

Custom AI Solutions

Production-grade applications and internal platforms when the opportunity is specific to your business and no vendor is going to build it for you.

Typical engagement

Phased builds, 8–16+ weeks

Larger implementations are delivered in phases with a usable system at the end of each. You own the code, the data and the infrastructure from day one.

Some opportunities are too valuable and too specific to buy. A pricing engine trained on your quote history. A knowledge system over twenty years of project files. A customer-facing product feature that competitors can’t replicate. These require real software engineering — security, data pipelines, evaluation, deployment, maintenance — not a prompt and a demo.

What we build

Internal AI platforms and copilots over proprietary data
Retrieval and knowledge systems with evaluation harnesses
AI-enabled features inside your customer-facing products
Data pipelines and integration layers
Model evaluation, observability and cost controls

Business outcomes

Proprietary capability that compounds over time
Systems your team can run, extend and audit
Vendor independence — model choice stays yours
Defensible IP and data posture

Engineering standards

Version-controlled, tested, observable, documented. Deployed to your cloud accounts. No credentials or data flow through ours.

Fractional AI Leadership

A senior AI lead and build capacity on retainer — the strategic and technical execution of an internal team, without hiring one before you know what it should do.

Typical engagement

Monthly retainer, quarterly commitments

Scoped as a share of a senior leader’s time plus engineering hours, with a roadmap owned jointly by Skeptics and your executive sponsor.

Hiring a Head of AI is a $300k+ decision made before most companies know what the role should own. A fractional lead gives you the roadmap ownership, vendor discipline and governance of that role today — and the build capacity to keep shipping — while the long-term org design becomes clear from results rather than guesses.

What’s included

Standing roadmap owner reporting to leadership
Quarterly opportunity reviews and re-prioritization
Vendor, model and architecture decisions
Governance, data and risk policies that fit your size
Ongoing build and improvement of deployed systems
Hiring and upskilling support when you’re ready to internalize

Business outcomes

Continuity between strategy and execution
Faster decisions with fewer false starts
Investment paced to proven returns
An exit path to an internal team on your timeline

FAQ Common questions

Straight answers.

How much does an engagement cost?

Discovery and assessment work is fixed-scope and priced as a project. Implementations are scoped against the opportunity they target, so the range is wide and depends on what we find. We will give you a specific number after the strategy call — and we will tell you if we think the opportunity doesn’t justify the spend.

Do we need clean data or a data team first?

No. Most mid-market companies don’t have either, and the best early opportunities are often the ones that work with messy documents and existing systems. Data quality becomes a priority when a specific, high-value opportunity requires it — not before.

Which AI vendors and models do you use?

Whichever fit the problem, your security requirements and your budget. We are not resellers and have no vendor commitments. Architectures are designed so you can change models without rebuilding.

Who owns what we build?

You do. Code, data, prompts, evaluation sets and infrastructure are delivered into accounts you control. We don’t hold your systems hostage with proprietary platforms.

Can you work with our existing IT team or MSP?

Yes, and we prefer it. We integrate with your team’s standards for security, deployment and support, and we document everything so they can run it after we’re gone.

Where are you based and where do you work?

Skeptics is based in Charlotte, North Carolina. We work with clients across the Southeast in person and nationally through remote engagements.

— Start here

Two ways to find out whether AI is worth your money.

Neither one is a sales pitch. Both end with a written point of view you can act on with or without us.

30 minutes · No cost

Discuss a Strategy Call

A working conversation about where AI could plausibly move your P&L — and where it probably can’t. You’ll leave with a clear next step.

Schedule a call → 2–4 weeks · Fixed scope

Request an AI Opportunity Assessment

A structured review of your operations, data and systems that produces a ranked list of opportunities with payback estimates and a build plan.

Request an assessment →