Practical AI and technology guidance
A fractional AI and technology advisor for small and mid-sized businesses that need clear priorities and useful systems — without hiring another full-time leader.
We cut through the hype, pick the right level of automation for where you actually are, and stay with you from conversation to roadmap to working system.
Choose the right level of help
A trusted outside perspective on where AI, automation, or better systems could actually help.
That discussion turned into a reviewed diagnostic, prioritized recommendations, and a written action plan.
Normally $1,000 — free for a limited time with a checkout code.
Claim your free assessmentWorkflow sprints and ongoing support when the right opportunity is clear and it is time to build.
We help decide where modern technology belongs in the business, where it does not, and what should be handled first.
We evaluate tools, workflows, risk, cost, and readiness so you are not chasing every new platform or overbuilding too early.
When an idea is worth pursuing, we can help shape the roadmap, design the workflow, implement the system, and keep improving it.
Hermes Desktop makes agent work feel more like an operating desk than a terminal experiment. Pair it with GLM 5.2 and businesses get a serious long-context model setup that is much cheaper to experiment with.
Retell is useful because it handles the phone workflow around the model: call routing, tools, testing, transcripts, and QA. GPT-Realtime-2 makes the voice layer better, but the real work is still deciding what the receptionist should and should not do.
Before you test another AI tool, define the workflow, owner, review step, and result you need the work to produce.
A useful AI advisor sets a weekly review rhythm so owners can catch issues, approve changes, and turn repeatable work into process or automation.
Use call transcripts to assign owners, draft follow-ups, flag approvals, and track what actually needs to happen next.
Notes
Most teams measure the wrong thing when they start using AI. They count prompts, tools, features, or experiments. The more useful early question is simpler: how many hours did we get back? Pick one task. Time it before AI. Time it after AI. Multiply by frequency. If the time savings are not visible yet, the tool may still be interesting, but it is not yet proving value clearly enough to justify going deeper.
Most people want AI to handle the impressive parts of work first. In practice, the highest-value use cases are usually the boring ones: the weekly report, the invoice cleanup, the follow-up email, the meeting summary, the repeated customer reply. Start with the work that feels repetitive, predictable, and a little annoying. That is often where the first real value is hiding.
Most teams that have been using AI tools for a while are paying for more than they are truly using. A simple AI tool assessment takes about two hours and helps you make better decisions. Start with spend. Pull every AI-related subscription or API charge from the last three months. Then ask two questions for each tool: What job does it actually help with? Who is using it now? That is more useful than asking who has access. For tools that still matter, decide whether they are personal productivity tools or real team infrastructure. If a tool matters across the team, it should have an owner, a reason it was chosen, and a basic standard for how it gets used. The goal is not just to cut spend. It is to understand what your team is actually doing with AI so the next decision is based on reality.
Learning Resources
Tools to Try