Questions leaders ask before changing how work gets done.

Consultants, contractors, and privately held businesses with revenues ranging from $500,000 to $100M.

Every engagement starts with a consult to discuss your situation and consider existing roadblocks and constraints. Pricing may include project-based work and consulting, custom solution design or setup fees with an ongoing support tier, or fractional leadership.

Building out automations, even if you know of one repeatable task, starts laying down the foundations for automating and building structured procedures in other areas of the business.

If you do not want to automate repeatable tasks, you do not have to. Think of automation and an AI-assisted workforce as a way to supplement your current workforce so they can focus on what is really important and not the mundane.

AI thrives in the nuance because it has near unlimited imagination as long as the driver has the vision. If you have the vision, AI can be an excellent partner in bringing it out into reality.

Predictions and machine learning can be inaccurate, but that is generally avoidable during a curation phase. Humans have been known to be inaccurate as well. The benefit of the LLM is that you can curate multiple ML models and see which one is most accurate for your intended purpose.

There are LLM solutions that can be internal only and not connected to the internet. A custom-built application with an LLM can also be internal. Cloud models generally trade off infrastructure cost for subscription, and cloud providers and model makers do offer private/non-used tenant spaces that allow your data not to be used.

This is no different than current software solutions or operating systems. There needs to be a security management strategy already in place so that when an LLM or AI is used, the same principles are applied. See NIST CSF 2.0.

Most providers have compliance-compliant tenant environments. Hosting an LLM locally is also a capability, though it can drive up infrastructure cost. The tradeoff is that you have full and total control of your data.

This is not a new problem. The build-vs-buy decision has always been there, and now the shift to building is more obtainable. Rather than using a solution that inhibits revenue growth, investing in a solution custom tailored to your environment can provide more business and process control that influences efficient operations.

Integration changes are rapidly evolving. We now have MCP along with APIs, which is a massive shift in how the industry will communicate. Successful businesses are successful because of the processes people are implementing. Technology is a tool to assist in that process, and it should be planned so the product can adapt quickly when another evolution happens.

Managed service providers and support contracts are not a new concept, and they should be looked at through what is best for your company. Some companies have the personnel to fine tune agentic automations while others are solo shops. The solution delivered needs to be built so you do not need daily fine tuning.

ChatGPT and Microsoft Copilot are in an entirely different category from what is currently available in the market. Those are seen in the automation space as helpful LLMs to chat with and maybe look some things up. Most tools that actually do automated tasks, collaborate data, and unify systems are other tools that are hot swappable but driven by coding assistant solutions.