Four ways to start, and the smallest one is about a month.

Enterprise Intelligence Proof of Concept

This is for you if...

"I like the idea. I am not committing to a program on a maybe."

The pain

You bought AI licenses for your developers. You cannot tell whether they are actually faster, because nobody measured, and nobody can agree on what "faster" would even look like. Meanwhile every vendor conversation ends the same way: a large proposal, a long timeline, and a request that you trust them. You are not being difficult. You are being asked to spend real money on a promise.

What you walk out with

• One of your real teams, working on one of your real codebases, with Enterprise Intelligence in place. Not a sandbox. Not a scripted demo.
• The flagship capability, running on your code. On one scoped piece of real work, you approve a plan and Enterprise Intelligence builds it in one long unattended run, checking its own output and fixing what it finds. You review what came back. The build system behind this is patent pending, and this is the thing the Proof of Concept exists to prove.
• Your conventions and your rules encoded, not generic best practices copied from somewhere else.
• A before and after you can put in front of your own leadership. You take the baseline at the start so the comparison is yours, not ours.
• A written scope and a cost ceiling for going further, so the next decision is a yes or a no, not another discovery process.
• You use Enterprise Intelligence for the whole engagement, and you keep everything you build with it. The code, the documents and the baseline your team produces are yours to keep and keep using, whether or not you go further. Enterprise Intelligence itself stays licensed rather than handed over, and the license is what keeps it current for you when you continue.

Shape

About a month. One team, typically five to fifteen developers. One codebase. A few hours a week from your people, not a full-time commitment from anyone. Your side needs one person who owns the decision, usually the engineering leader who runs that team.

Three steps to start

1. Book a 30-minute call at encephalon.net/book. You find out in thirty minutes whether this is a fit. If it is not, you hear that on the call.
2. Name one team, one codebase, and one owner.
3. Kick off within two weeks of signing. You have your before and after in about a month.

Enable Your Development Teams

This is for you if...

"AI is already in our developers' hands. What comes out of it is inconsistent, and nobody is accountable for that."

The pain

Every developer uses the AI differently, so your codebase is drifting in as many directions as you have developers. Code review has quietly become the place where you catch things a written rule should have caught, which means your senior people are spending their weeks cleaning up instead of building. Nobody can tell you whether the AI is respecting your security requirements. Onboarding still takes weeks. And the institutional knowledge that keeps all of this from falling apart is sitting in three or four people's heads, one of whom is thinking about leaving.

What you walk out with

• Long unattended builds as a normal way your team works. Your people approve a plan and the build runs without anyone sitting over it, checking its own output and fixing what it finds. This is the flagship capability, the build system behind it is patent pending, and this engagement is where it becomes something your team uses every week rather than something you saw once.
• Your standards, security rules, and architecture patterns applied on every Claude Code session, across every team, without anyone policing it.
• Control over what AI can touch in each environment, so the security conversation is settled instead of deferred.
• New people productive in days. Your onboarding stops being a six-week context transfer.
• Your own people trained to extend it. You are not buying a dependency. You are buying a capability your team owns and grows.
• The measurements to prove it worked, taken against the baseline you set on day one.

Shape

Four to twelve weeks, depending on how many teams you have and how much of your way of working is already written down. A single-team company can be live in under a week. A company with a dozen teams and real compliance obligations is at the longer end. Your teams keep working the entire time. There is no freeze and no big-bang cutover.

Three steps to start

1. Book a 30-minute call at encephalon.net/book. Bring the person who owns engineering standards.
2. Half a day with your team to see how you actually build today, not how the wiki says you do.
3. You get a scope, a timeline, and a ceiling for that scope. The ceiling goes in the contract. Then you decide.

Data and AI Roadmap

This is for you if...

"Leadership wants an AI strategy. I need to know which of these ideas are real before I put my name on one."

The pain

You have a list of AI ideas from every corner of the business. Some of them are good. Some of them cannot possibly work, and you suspect you know which, but you cannot prove it in a meeting. Underneath all of it is a question nobody wants to ask out loud: is our data actually in a state where any of this would function? So either nothing gets funded, or the wrong thing gets funded, burns a year, and quietly dies. That failure gets remembered longer than the idea did.

What you walk out with

• A ranked list of your AI opportunities, scored on what they are worth to the business, with the ones that will not work honestly marked as such. The "no" list is worth as much as the "yes" list.
• A straight answer about your data. What is ready, what is not, and specifically what has to be built or repaired in your data layer before the features on your list can work. No hedging.
• The dependency map. Which data work has to happen before which AI feature can possibly work. This is the thing that quietly kills AI projects halfway through, and it is knowable in week two.
• A sequenced plan with rough effort and cost per step, ordered so you get something usable early instead of waiting for the end.
• A readout you can take straight to whoever approves the money, board, executive team, or your co-founder, without rewriting it first.

Shape

Two to six weeks. The length depends on how many parts of the business you want covered, because the work is mostly conversations with your people: finance, operations, engineering, whoever actually does the job. You need one person with the authority to get those people in the room. At a large company that is an executive sponsor. At a sixty-person company that is usually the founder, and it takes an email.

How this connects to the next one

The Roadmap is step one of "Enable Your Entire Organization." If you go on to the full rollout, this is where it begins, and nothing gets repeated.

It is also fine to buy it and stop. Plenty of organizations need the map more than they need a guide. Everything you get is yours to execute however and with whomever you like.

Three steps to start

1. Book a 30-minute call at encephalon.net/book. Bring the executive who can convene other departments.
2. Agree which parts of the business are in scope. More departments means more weeks, and you control that dial.
3. Interviews start within two weeks of signing. Readout to your leadership in two to six.

Enable Your Entire Organization

This is for you if...

"We made engineering faster and now everything downstream is on fire."

The pain

Speeding up your developers is a good thing, right up until it is not.

When one team doubles its output, the work does not disappear. It piles up in front of everyone else. Testing takes longer than the build did. Contracts sit for two weeks waiting on whoever handles legal. Invoices are still reconciled by hand. The same report gets rebuilt every month. Support is still answering the same forty questions. At a two-thousand-person company those are five departments. At a sixty-person company they are three people, and one of them is you.

You paid for speed and what you bought was a bigger queue in front of the people who were already the bottleneck. Meanwhile the departments that never got the tools are watching engineering get all the investment and drawing their own conclusions about where they stand.

The fix is not to slow engineering down. It is to stop treating this as an engineering purchase.

What you walk out with

• The Roadmap first, so you know which departments have the biggest gap between effort spent and value produced, which ones your data can actually support, and what has to be built or repaired in your data layer before the rest is worth starting.
• Department by department rollout, in waves, ordered by what pays back soonest. Each wave stands on its own. You are never waiting for a big-bang finish to get value.
• The same organizational knowledge available to everyone, not just to developers. Your analysts, your operations people, and your project leads work from the same source of truth.
• The same guardrails everywhere. One set of rules about what AI can and cannot do with your data, applied across the company rather than negotiated per department.
• Your own people running it. Wave after wave, your team owns your standards and conventions inside the tool. We keep the tool itself current: updates, new tooling, and migration help the week a new model ships.

Shape

The Roadmap comes first, at two to six weeks. Rollout follows in waves after that, typically one to two quarters for a mid-sized company, longer if you are large or heavily regulated. You approve each wave before it starts, and you can stop between any two of them. There is no all-or-nothing commitment at the front.

Three steps to start

1. Book a 30-minute call at encephalon.net/book. Bring the executive who owns the outcome across departments.
2. Start with the Roadmap. It is the first wave, it is priced on its own, and it tells you whether the rest is worth doing.
3. Approve wave one. Then decide about wave two when you have seen wave one land.

What is true of every engagement

• You get a scope and a ceiling before you commit. Both go in the contract. The ceiling covers the scope we agree to, and the only thing that moves it is a change you ask for and approve in writing first. No surprise invoices.
• Nothing is a black box. Everything built is written in formats your team can read, change, and keep.
• Your people learn to run it. They own your standards and conventions inside it. We keep it current, with new tooling and migration help layered on as new models ship.
• Your license keeps you current. Enterprise Intelligence is licensed, and the license is what keeps updates flowing to you. That matters most the week a new model ships: your team gets the benefit of it without a migration project and without rebuilding anything.
• You can stop between phases. Nothing here requires you to buy the whole path up front.