Stop piloting. Start operating.
Most enterprise AI stalls the same way: promising pilots, rising complexity, nothing in production. We engineer the context, governed agents, and human-in-the-loop controls that move AI from experiment to the way your business runs, the same system we built and run our own company on.
AI products we built and run our own company on: Memra, Bott, Foyer, Quire, Fynn
audit-effort reduction across a 500-site enterprise Drupal fleet
delivery streams across Ansible, Python, APIs, and enterprise infrastructure
The pilot graveyard is full of good intentions.
Every organization has tried AI by now. Most have the same scar tissue: a chatbot nobody trusts, a copilot license nobody renews, a POC that demoed well and shipped never. The pattern isn't a tooling problem. It's an engineering problem.
A better prompt won't save a system that doesn't know you.
Generic models don't know your customers, your decisions, your voice, or your rules. Without memory and integration into your sources of truth, AI stays a guessing engine.
Demos aren't systems.
A prompt that works once isn't a workflow. Without state, governance, and integration into real systems of record, AI stays a party trick.
Procurement asks where AI runs.
RFPs now ask exactly where AI runs, what it can touch, and who reviews its output. "We use ChatGPT" is not an answer that passes review.
The organizations getting value didn't find a better tool. They engineered a system.
Four offerings. One engineering model.
We invest in understanding where AI is actually stuck in your business before we build, then engineer the context, agents, and controls around that.
AI Strategy & Readiness
Find where you actually stand, prioritize use cases that survive contact with production, and leave with an architecture, not a slide deck.
Agentic Systems & Context Engineering
Governed agents in the heart of your operation, built on the same patterns as Memra, Bott, Quire, Foyer, and Fynn. Context layer first, then agents that hold state and act.
AI in the Digital Experience Platform
Classification, AI search, recommendations, and governed content generation, engineered into Drupal, Acquia, and the DXP your editors already use. AI in the platform, not bolted beside it.
AIOps & AI-Accelerated Modernization
Embedded automation strategists running AIOps across enterprise infrastructure, plus migrations where AI compresses the timeline, not the review gates: scope grooming, pattern transfer, code generation, human-validated cutover.
Not pilots. Production.
AI is the engagement.
A dedicated AIOps delivery stream where automation strategists build Ansible playbooks, Python automation, and API integrations across internal infrastructure. This is not AI-assisted work. AI is the work.
License cliff to live cutover.
An Eloqua to HubSpot migration with a non-negotiable expiry date and no prior hands-on HubSpot experience. AI groomed scope, guided platform navigation, selected the Forms API to preserve attribution, and generated the integration module before QA against the live EU instance.
1,500 hours down to 83.
A migration audit accelerator for a 500-site Drupal fleet cut analyst effort by 94%, moving per-site review from three hours to ten minutes with Acquia Cloud APIs, Playwright visual QA, Claude, and tokenized coverage analysis.
AI inside the QA loop.
AI-generated Playwright workflows target a 30 to 40% reduction in manual scripting time, with reusable templates, AI-powered locators, refactoring patterns, and documentation for Drupal delivery teams.
We didn't buy our way out of the knowledge problem. We engineered out of it.
Every company's knowledge dies the same way: a decision in Slack, a contract in one tool, a transcript in another, gone in six months. We rebuilt ourselves as an agentic system. Every pattern we sell, we run daily.
Memra
Institutional memory, made machine-readable. An entity layer gives every account, engagement, and person a canonical identity, and every decision is indexed against it. Ask anything and it answers with cited evidence, and flags what it doesn't know.
- 1
- entity layer, canonical identity for every account, engagement, person
- 6+
- signals unified: Slack, CRM, docs, tickets, PRs, transcripts
- Live
- delivery risk, capability research, account intelligence, proof retrieval
- BottThe engagement agent
Joins the project day one and links every decision to the code it shaped, then acts: PR review, incidents triaged into fix PRs, dependency reviews, DORA metrics to every steering review. Scoped permissions, default-deny, full audit logs.
PR reviewIncident triageDORA metrics - QuireThe growth engine
AI-run demand generation grounded in Memra's context. Research, creative, and launch compressed from weeks to hours, personalized one to one, not by segment.
ResearchCreative1:1 personalization - In buildFoyerCustomer experience layer
Personalized deal rooms and lifecycle intelligence. One branded, intelligent surface for the whole customer journey.
Deal roomsLifecycle intelBranded surface - In buildFynnThe people platform
The same context architecture, pointed at talent: AI-native recruitment, growth paths, and people operations, delivered with humans in the loop.
RecruitmentGrowth pathsPeople ops
AI-native means superhuman speed. AI-native delivery demands the best humans in the loop. The result: faster iterations, higher quality, and a partnership that actually feels like one. This is what that looks like as architecture: context at the core, governed agents around it, humans owning judgment. We bring the same architecture to yours.
AI you can put in front of procurement.
Every AI system we build ships with its governance: default-deny permissions on actions, per-tenant isolation, structured audit logs, and human-led review on architecture, security, and release decisions. When RFPs ask where AI is used and how it's controlled, and they now do, our clients have the documented answer.
- Why engineering context will define the future of AIRead →
- How we used AI to transform discovery into actionable architectureRead →
- How we rebuilt our IPL prediction game with Claude in 2026Read →
- How our open-source plugin made our Drupal delivery more predictableRead →
- How we automated 80% of the SDLC with AI (video)Read →
Redesign how AI works for you.
Whether you're holding a stalled POC, a procurement question you can't answer, or a roadmap that assumes AI without engineering it, let's design the system, not the demo.
The same team carries it through.
We don't hand the work to a build partner and walk out. The people who frame the bet are the people accountable when it ships. Read how the other capabilities plug in.