Services · AI Advisory & Adoption

You don't need more AI. You need to know which AI, and why.

Most businesses have bought tools and gotten experiments. We tell you exactly what to adopt, what to skip, and in what order. Then we stay until it pays. If your team has bought AI tools and can't tell you what they're returning, this is where to start, whatever your size.

Book a diagnostic →All services

The adoption gap

Most AI spending is not working.

The tools exist. The experiments have happened. The results are not compounding. The gap between buying AI and operationalizing it is where most businesses are stuck, and it is not a tools problem. It is a sequencing, selection, and adoption problem. That is exactly what this engagement solves.

70%

of businesses are stuck in the experimental phase of AI adoption

SBE Council, 2026

27%

of small businesses feel confident adopting AI into their operations

2026 survey data

61%

cite cost and unclear ROI as the top barrier to AI adoption

2026 survey data

$18K

average annual waste on disconnected AI tools per business

Industry estimate, 2026

What advisory covers

Every dimension of the adoption question.

From readiness to roadmap to the people side. Advisory is not a single deliverable. It is a complete engagement that closes the gap between where your operation is and where it needs to be.

AI Readiness Assessment

A structured audit of your current tools, workflows, team capability, and data posture. Not a scorecard for its own sake: the output is a ranked gap list and a clear entry point into the generative, autonomous, or agentic tier that matches where your operation actually is.

Use-Case Discovery & Prioritization

We interview the people doing the work and map every candidate use case against three criteria: dollar value of the problem, probability of AI solving it well, and implementation risk. You end up with a ranked list, not a wish list.

Tool & Platform Selection

A structured evaluation of the platforms and point tools relevant to your use cases: feature coverage, integration surface, data residency, pricing model, exit risk. You get a recommendation with the reasoning written out, not a logo grid.

LLM & Model Selection

Model-agnostic across Claude, GPT, Gemini, Llama, Mistral, and the broader open-weight ecosystem. We map the right model to each task by cost, latency, capability ceiling, and compliance requirement. No vendor allegiance, no hidden commissions.

Build vs. Buy Decisions

For every capability gap, a structured comparison of build cost, buy cost, integration complexity, and long-term control. The answer is not always buy. When it is, we tell you which vendor and why, with the assumptions written out so you can audit them.

Vendor Evaluation

We tell you what not to buy as clearly as what to buy. We evaluate contracts, integration terms, data ownership clauses, and roadmap credibility. If a vendor is over-promising, we name it before you sign.

Adoption Roadmap & Sequencing

A phased build plan with each initiative sequenced by ROI and dependency. The readiness assessment places your operation on the Crawl, Walk, or Run tier: generative tools for Crawl, autonomous workflows for Walk, agentic systems for Run. The roadmap moves you up in order, not at random.

Team Training & AI Fluency

Role-specific training that closes the gap between tool availability and actual use. We train people on the tools they will use, in the workflows they already run, not generic AI literacy sessions disconnected from the work.

Change Management

Adoption fails at the people layer more often than the technology layer. We design the rollout sequence, handle stakeholder communication, and build the internal feedback loop that catches resistance before it becomes abandonment.

AI Policy & Guardrails

A written policy covering acceptable use, data handling, model output review, and escalation paths. Designed to be workable, not just defensible. Your team reads it and knows what to do.

ROI Measurement & Proof

We define the measurement framework before anything is built: the baseline, the metric, the expected delta, and the review cadence. Every initiative enters with a success criterion. Every quarter produces a number, not a narrative.

The Fractional AI Officer Seat

A standing place in your operating cadence. We own the adoption roadmap, run the biweekly reviews, and report monthly on what moved: time saved, cost reduced, revenue attributed. This is not a retainer that produces decks. It is an operator seat with accountability.

How it runs

Assess and Architect first. Then you decide.

Advisory maps to the first two phases of the Krastor Method. You get the full assessment and a phased roadmap before any build begins. The roadmap is yours: take it to your own team, a third-party developer, or us. No lock-in.

Step 1

Assess

We audit your current tools, team capability, data posture, and use cases. The output is a ranked gap list and a named dollar figure for the cost of doing nothing.

Step 2

Architect

We design the adoption roadmap: phased by ROI, sequenced by dependency, with each initiative placed on the generative, autonomous, or agentic tier where it belongs.

Step 3

Build & Align

When you want the fix built, we build it, or we hand the documentation to whoever is building it. Training and change management happen here, alongside the technical work.

Step 4

Amplify

The roadmap compounds. Each phase builds on infrastructure the prior one paid for. Measurement is built in from the start so every quarter produces a number, not a narrative.

Read the Krastor Method in full

Questions

Straight answers.

Do we have to hire you to build it?

No. The advisory engagement produces a roadmap that is yours to keep and execute however you choose: your own team, a third-party developer, or us. There is no lock-in. If you want us to build it, that is a separate scoped engagement. If you want to hand it to your own people, the documentation is written for that.

We already bought AI tools. Is it too late?

No. That is the most common starting point. Most of the businesses we work with arrive with a mix of tools they are underusing, tools they are overpaying for, and gaps they did not know they had. The assessment maps all three and tells you what to keep, what to cut, and what is still missing.

How is this different from the diagnostic?

The diagnostic is the free 30-minute entry call: it produces a written map of the constraint and confirms whether the problem is worth a larger engagement. Advisory is what follows when the adoption question is bigger than one call can answer. It is the full engagement: assessment, roadmap, training, policy, and measurement framework.

Do you sell or resell software?

No. Krastor does not take markups on software, does not hold reseller agreements with vendors, and does not earn commissions on recommendations. Every tool recommendation is clean. The only thing we are selling is the work.

Will you train our team?

Yes. Fluency and change management are core to the advisory engagement, not add-ons. A roadmap that no one adopts is not a success. We train the people who will use the tools, in the workflows they will use them in, and we design the rollout so adoption sticks.

Continue

Strategy

Diagnostics, growth roadmaps, and the revenue audit that names what the adoption gap is costing you.

Explore

AI Enablement & Training

Role-based fluency programs and change management for teams who need more than a roadmap.

Explore

AI Architecture

The build phase: agents, governance, and model-agnostic systems that execute the roadmap advisory designs.

Explore

Engagement starts here

Start with the diagnostic.

Thirty minutes. We map your operation, name what's actually slowing it down, and tell you what we'd do if we were running it. You get a written stack assessment after the call, whether you hire us or not.

Book a Diagnostic Take the AI Readiness Assessment

Not limited to what's listed. Every engagement starts by assessing what your business actually needs, and we build whatever it requires.