# Consulting & Technical Strategy

We make the technical calls that are expensive to get wrong, then build it or lead the team that does.

## The problem

Growing businesses face technical decisions that shape their next few years. Build custom software or buy SaaS. Hire a full engineering team or contract. Adopt AI now or wait. These decisions are expensive to get wrong, and some companies make them without anyone in the room who has shipped production software across enough contexts to know what actually works.

## What we do

### Build-versus-buy advisory

We evaluate whether your workflow needs custom software, an off-the-shelf product, or a configured wrapper around an existing tool. The answer depends on how central the process is to your business, how much the available products fight your operations, and what the ongoing maintenance cost looks like for each path.

### Technical strategy and architecture

We define the technical approach before code gets written. Stack selection, infrastructure design, integration planning, and build sequencing so the engineering work starts in the right place and does not need to be redone when requirements sharpen.

### Fractional and interim engineering leadership

For teams that need senior engineering direction but are not ready for a full-time hire, we provide fractional CTO or engineering lead capacity. We set technical direction, manage vendor relationships, run hiring, and make the architectural calls that a growing product needs.

### Embedded and forward-deployed engineering

A senior engineer joins your team on contract for as long as you need and works inside your codebase and processes. They set direction, review pull requests, and ship features alongside the engineers you already have.

### AI environment setup and workflow automation

We set up AI environments your team can actually use: configuring tools like Claude Code or Codex for internal workflows, building MCP services that connect to your existing CRM or operations software, and training your staff to operate and extend the system themselves.

## How we work

### 01 Assessment

We map your current operations, identify the decisions that need to be made, and produce a clear recommendation with trade-offs for each path. This is often where the value lands. If the recommendation is to buy rather than build, you have your answer and we part ways.

### 02 Planning

If the recommendation involves building or integrating, we produce a technical plan with scope, sequencing, and cost estimates. The plan is detailed enough that you could hand it to another team if you chose to.

### 03 Execution

We build it, lead your team through the build, or oversee a vendor doing the work. The engagement shape depends on what you need and what you already have in house.

### 04 Handover and support

We document everything, train your team, and remain available for ongoing advisory as your needs change. The goal is independence, not dependency.

## Proof

### AI Environment Setup for Professional Firms

We worked with multiple professional firms to make their practices more efficient with AI. Each engagement started with discovery, identifying which tasks in the practice could be automated or streamlined.

We then helped each firm stand up an AI environment that their staff could use and maintain themselves, configured for bespoke tasks specific to their practice. The work went beyond core professional tasks to include sales workflows, organization systems, and general time-saving automation.

Every implementation was designed with privacy law and client confidentiality as primary constraints. The pattern across these engagements was consistent: assess what to automate, build the environment, and set it up so non-technical staff can operate and update it without engineering support.

Read more: Build vs Buy, when to build software and when to buy SaaS

## Technical depth

Our advisory work draws on production experience across the full application stack. We have shipped on Next.js, React, NestJS, Python, and Node.js for applications, PostgreSQL and Redis for data, AWS and Vercel for infrastructure, and OpenAI, Anthropic, and open-source models for AI. When we recommend a technical path, the recommendation comes from having built and operated systems on that path, not from reading vendor documentation.

For AI consulting specifically, we configure environments using the tools that fit the workflow: hosted LLMs for general knowledge tasks, RAG pipelines for domain-specific retrieval, and workflow automation tools where the goal is to chain multiple steps together with human oversight at the right checkpoints.

## FAQ

### How is a consulting engagement scoped and billed?

Assessment engagements are scoped and priced before we start. Ongoing fractional leadership is billed monthly. We do not upsell into larger builds unless the assessment genuinely recommends one.

### Do you only consult, or do you also build?

Both. Many engagements start as advisory and move into build work when the recommendation calls for it. We also consult without building when that is what you need. The assessment is honest regardless of whether we stand to earn build revenue from the outcome.

### What size companies do you work with?

Companies at every stage, from early startups to established businesses and enterprise teams. Some have technical staff and need senior direction, and some need one architectural decision made or a new initiative scoped.

### Can you work with our existing developers?

Yes. A common engagement shape is advisory and architecture with your team handling implementation. We set direction, review pull requests, and unblock architectural decisions without displacing the engineers you already have.

### Can you join our team for a set period?

Yes. We work as contract engineers or engineering leads inside your team, and we agree the length and scope with you before we start.

### How is this different from a management consultancy?

We write code. Our recommendations come from building and operating the systems we advise on, not from frameworks and slide decks. When we say a particular approach will work, we can point to production systems where we made it work.