How We Work

A phased path from AI uncertainty to positive ROI

Align
Build shared AI language, governance, and a clear view of where AI fits.
Validate
Prove one workflow against your real data, systems, and economics.
Build
Ship your first intelligent asset into production.
Maintain
Keep it secure, current, and improving.

All the speed of AI without the risks

We build production AI systems for established companies that can't afford a failed experiment. Our engineers have shipped 150+ AI projects on AWS, OpenAI, Anthropic and more. Every engagement runs under SOC 2 Type II and HIPAA-compliant controls. You get working AI in weeks, on your data and in your workflows, without putting customers or compliance at risk.

A central 923 icon connected by lines to five surrounding white circular icons representing AWS, OpenAI, AI, and two other logos, along with badges for SOC 2 Type 2 compliance and HIPAA compliance, below which is a label reading '150+ projects'
150+
AI systems shipped to production, not left in pilot.
98%
delivered on time and on budget. Speed you can plan around.
13+
years building software for established companies since 2012.
8+
model providers we build on. Use the best fit, never get locked in.
our data-backed process

We guide your team through our proven process

Remove the uncertainty and reduce overwhelm by following our framework that has helped over 150 organizations become AI native.

01

Align

The most important part of the project happens before any code is written

In Align, we work with your leadership team to build AI fluency, set governance, and identify where AI creates real value in your organization.

1

Executive AI fluency

What AI is and what it isn’t. The range of models available, from OpenAI to Claude to Gemini. Where AI fits in your operations and where it falls short. A framework for which opportunities to pursue.

2

Practical AI mastery

Production-grade prompting techniques on your own business data. Hands-on with ChatGPT, Claude, and data analysis tools. The difference between naive prompts and deployed production prompts, with a live exercise on your own data.

3

Governance and Shadow AI audit

Audit your systems for Shadow AI usage. Assess AI readiness and gaps. Draft an AI Constitution that defines acceptable use, data-handling rules, and a roll-out plan.

02

Validate

We test feasibility, model costs, and work with your data to produce concrete answers

In Validate, we run a Rapid Validation Sprint that proves one workflow against your real data, permissions, and economics.

1

Workflow and data investigation

Map current workflows against future-state flows. Test data viability and retrieval quality. Run workshops on your current workflows and their costs. Examine permissions, integrations, and legacy systems for compatibility.

2

Architecture and economics

Produce an architecture and infrastructure analysis. Look at whether to use boilerplate or custom builds. Model the economics before recommending a path forward.

3

Requirements and roadmap

PRD, user stories, and key UI screens. An ROI model that prices the build. A Phase-1 roadmap with scope and deliverables defined.

4

Working prototype

A working prototype running on your own data, so you can see the workflow in action before committing to a build.

03

Build

Ship the first intelligent asset

In Build, a dedicated pod turns the validated blueprint into production software you own.

1

Your owned intelligence layer

A natural-language interface over your approved documents, databases, and legacy systems. Workflow and SQL agents that retrieve, compare, summarize, and execute approved steps. Agentic digital workers that meet people where work happens.

2

Accelerated with boilerplates

Proven foundations for auth, chat history, admin, logging, deployment, and integrations. You don't pay to reinvent common plumbing. Your budget goes toward what's specific to your business.

3

How we build

Our engineers direct AI agents to iterate against a definition of done until the work is ready for human review. Every discipline runs evaluation suites tracked as a KPI, because AI outputs are probabilistic. A two-sided loop keeps human judgment in the process.

4

Operationalize legacy knowledge

Clean, tag, and structure messy PDFs, transcripts, drives, and SharePoint. Pull hard facts from systems of record before generating text. Refuse data a user can't already access, with instant revocation on offboard.

5

Secure and model-agnostic

Entra/O365 permission mapping with role-scoped retrieval. Private cloud deployment with hardening, audit, and observability. Swap or route between GPT, Claude, and Gemini without changing the employee experience. Integrates with M365, ERP, CRM, and SharePoint.

04

Maintain & Monitor

Keep it secure, current, and improving

In Maintain & Monitor, we keep your intelligent asset secure, reliable, current, and improving.

1

Monitoring

We monitor the system with Sentry, Mixpanel, Amplitude, Plain, and our own monitoring tools. We track system health, security, and performance.

2

Usage analysis

We analyze usage patterns to understand how your team interacts with the system and identify opportunities for improvement.

3

Model upgrades

We upgrade models as new versions arrive, keeping your system current with the latest capabilities.

4

Education and support

Education continues as a throughline. Your team learns to operate and extend the system, whether we manage maintenance jointly or transition to your internal ownership.

Start your data-backed AI transformation

You've seen how we work. Let's apply it to your organization.