SERVICES

Start small. Get a decision or a result.

Applied FutCo AI starts with workflow economics, operational constraints, and risk tolerance, then matches the engagement to the amount of work needed to get to a clear result.

AI Opportunity Audit

Best when your team sees several possible AI use cases but needs a clear view of which workflows are worth pursuing, what the risks are, and how to sequence the work before committing to implementation.

What it includes

  • Stakeholder interviews and workflow review.
  • Tool, data, and process inventory across the target workflow.
  • AI opportunity and risk assessment.
  • Prioritized roadmap with one concept demonstration where feasible.
  • Executive readout with the next decision clearly framed.

Expected process

  • Understand how work currently moves through the business.
  • Identify where time, handoffs, and information loss create the most drag.
  • Rank opportunities by value, feasibility, and risk.
  • Deliver a roadmap the leadership team can use immediately.

AI Business Upgrade Sprint

Best when the business is ready to move from exploration to implementation and wants one or two useful workflows delivered with controls, training, and measurable outcomes built in.

Typical deliverables

  • Leadership and workflow discovery sessions.
  • Current-state workflow map and ranked opportunity matrix.
  • Success metrics and baseline measurements.
  • One or two implemented AI-assisted workflows.
  • Human approval, logging, and fallback controls appropriate to the use case.
  • Team handoff, training session, and a 90-day roadmap.

How the Sprint works

  • Clarify the workflow, stakeholders, and desired business result.
  • Define the right mix of AI, automation, software, and employee review.
  • Implement the smallest useful production workflow.
  • Train the team, measure the result, and document what comes next.

AI Care Plan

Best for teams that already completed a Sprint and want a lightweight way to keep a shipped workflow stable, current, and improving without moving into a broader advisory relationship.

What is included

  • A defined monthly hour bank for troubleshooting and light optimization.
  • Small workflow adjustments as models, APIs, or internal processes change.
  • Priority response when a shipped workflow breaks.
  • A brief monthly usage and health summary.

How it differs from Fractional AI Leadership

  • The Care Plan keeps a delivered workflow healthy rather than owning the full AI roadmap.
  • It is designed for maintenance, light improvement, and operational continuity.
  • It does not assume broader governance, vendor management, or cross-team program leadership.

Fractional AI Leadership

Best when a company needs sustained AI direction, architecture oversight, governance, and implementation leadership but is not ready to hire a full-time internal AI executive.

Typical responsibilities

  • Maintain the AI roadmap and opportunity backlog.
  • Select and manage tools, vendors, and implementation priorities.
  • Establish security, privacy, and governance practices.
  • Review system performance, failures, and changing model behavior.
  • Coordinate internal stakeholders and external implementers.
  • Track adoption and business results over time.
  • Turn the workflows and knowledge already organized during an Audit or Sprint into a system your approved AI tools can draw on directly — the same pattern we run internally today.

Engagement style

  • Scoped to your team's size and involvement rather than treated as an open-ended retainer.
  • Blends advisory work, implementation oversight, training, and incremental improvement.
  • Keeps optionality intact while building systems the company can actually operate.

Additional capabilities

Some companies need a supporting engagement before or after a core service. These capabilities stay tied to actual workflows rather than generic AI theater.

  • Executive AI coaching and decision support.
  • Team workshops and role-specific training.
  • Custom knowledge assistants grounded in approved company sources.
  • Private, locally-hosted open-source models — fine-tuned on your own data over time — for businesses that cannot send data to third-party AI providers.
  • AI-assisted software-development enablement.
  • AI policy, governance, and tool-spend reviews.
  • On-chain intelligence and blockchain-related systems through E3D.

What makes a good first workflow?

The strongest first projects usually share most of these characteristics:

  • The workflow happens often enough that improvement will matter.
  • The work is time-consuming, repetitive, or information-heavy.
  • The business can define what a good outcome looks like.
  • The required documents, systems, or source material can be accessed reliably.
  • An employee can review important outputs or actions at the beginning.
  • The before-and-after result can be measured in time, throughput, quality, or responsiveness.

Frequently asked questions

Do we need an AI strategy before contacting you?

No. The first step can be identifying where AI is useful and where it is not.

Why not just use ChatGPT or Copilot ourselves?

Many companies already do, and that's a fine starting point. The limit isn't the model — it's that ad hoc use rarely connects to your systems, has no shared process across the team, and gives you no way to know whether it's actually saving time or money. That's the gap this closes.

What does this cost?

Engagements are fixed-scope and sized to the work. An AI Opportunity Audit typically starts around $2,000; an AI Business Upgrade Sprint typically runs $9,000–$25,000 depending on scope. You'll get an exact number before any commitment, and the Audit fee is credited toward a Sprint if you proceed within 90 days.

Do you work with the tools we already use?

Usually. The preferred approach is to improve existing work with the smallest reasonable amount of new infrastructure. Feasibility depends on access, APIs, data quality, and security requirements.

Are you tied to one AI vendor?

No. Recommendations are based on the workflow, data, risk, budget, and maintainability requirements.

Can you connect our AI tools directly to our company knowledge?

Yes, for clients who've already done the underlying work — this isn't a starting engagement. It depends on the workflows and knowledge organized during an Audit or Sprint, then extended under Fractional AI Leadership. We run the same pattern internally today to keep our own AI coding sessions current on our systems, so this isn't theoretical.

Can you avoid sending our data to an outside AI provider?

Yes. When data sensitivity requires it, we can deploy open-source models on your own infrastructure so nothing leaves your network. Those models can also be fine-tuned on your own data over time, so they keep improving with use instead of staying static.

Will AI act without employee approval?

Only where the action is low-risk and the customer explicitly wants that behavior. Consequential actions should begin with human review and clearly defined boundaries.

Can you guarantee a particular return?

No. Applied FutCo AI establishes baselines and measurable objectives, but results depend on the workflow, data, implementation, adoption, and broader business conditions.

Do you offer training without implementation?

Yes, although role-specific training connected to actual company workflows generally produces more lasting value than generic instruction.

Do you work with blockchain or cryptocurrency companies?

Yes — this is core territory, not a side offering. FutCo also builds and operates E3D, an on-chain intelligence and AI-agent platform, so blockchain-adjacent implementation work draws on systems we run ourselves, not theory. Any blockchain engagement is technical or operational in nature and does not constitute investment advice.

Ready to identify the next useful step?

If you already know the workflow you want to improve or need help narrowing the choices, we can use an introductory conversation to determine the right starting point.