// enterprise

We translate AI ambition
into production deployments.

Mid-market to Fortune 500. You've got the budget, the licenses, the strategy decks. What you don't have is the operator who can ship one of these pilots into production. That's us. We work inside your security boundary, ship inside your release cadence, and hand off to your team.

// what slows you down

The specific things enterprise operators tell us they wish were already fixed.

Pilots that never made it out of pilot

Two years of 'AI exploration' produced demos, not systems. We deploy narrow production slices with measurable outcomes from day one. If it doesn't move a number in 90 days, we don't keep it.

Vendor sprawl + integration debt

Four CDPs, three marketing automation tools, two BI stacks. We don't sell you more tools — we build the integration layer that makes what you already paid for actually deliver.

Security review cycles kill momentum

Six months of review before a vendor goes live. We deploy patterns your CISO has already approved — private models, BYOK, audit logs, SOC 2 posture — so reviews shorten.

GTM ops is fragmented across BUs

Each division has its own intake, qualification, nurture. We build the shared infrastructure layer that respects BU autonomy but eliminates redundant tooling.

// we know the stack

We've already worked inside your tools.

Enterprise stacks vary, but the categories repeat. We've worked inside the major platforms in each layer — and the integration patterns translate.

SalesforceMarketo / PardotHubSpot EnterpriseSnowflakeDatabricksSegment / mParticleLooker / TableauServiceNowOkta / Auth0WorkdayAdobe Experience PlatformAWS / Azure / GCP
// pilot to production

The 8 things production AI requires that pilots quietly skip.

Pilots win demos. Production wins budgets. The difference is the eight items below — none of which are interesting until the day they aren't there. We build to all eight from day one because the cost of bolting them on later is roughly the original engagement, twice.

01
Evaluations + regression tests
Repeatable scoring against a held-out set. The reason production output stays stable when the model upstream changes.
02
Observability + audit logs
Every input, output, tool call, and decision traceable. Required for both debugging and compliance posture.
03
Cost + token governance
Per-tenant, per-feature spend caps. Stops a single bad prompt loop from spending your quarter.
04
PII scrubbing + data residency
Pre-flight redaction. Region-locked inference. The lines your DPO will draw on day one.
05
Role-scoped tool access
Agent can only touch the systems its role permits. RBAC enforced at the tool layer, not the prompt.
06
Human-in-loop escalation paths
Confidence thresholds + structured handoff to humans. The default-safe behavior when the model isn't sure.
07
Versioning + rollback
Prompts, models, tools, and chains versioned with one-click rollback. Treat AI artifacts like code, not config.
08
Internal documentation + handoff
Runbook, eval suite, change log written for your team to inherit. We leave; the system stays operable.
// what we'd build for you

Custom software, built for your workflow.

Enterprise stacks rarely lack tools. They lack the connective tissue and the production-grade glue that turns capability into outcome. That's what we build — and what we hand off to your team to own.

Integration layer for the stack you already own

Connect the 12 SaaS tools each BU runs into a unified event bus. Stops the 'we have the data somewhere' problem without forcing a platform migration.

Internal admin console for AI workflows

Operations control center for the AI systems we deploy — prompt versions, eval results, cost dashboards, rollback controls. The thing your platform team will want from day one.

Attribution + revenue dashboard

Closed-loop attribution from first touch to closed revenue, BU-aware. Finance and marketing read the same numbers and stop having the same fight every QBR.

Custom AI agents with role-scoped tool access

Production agents trained to your workflow with explicit tool permissions, audit trails, and SSO-aware identity. The pattern your security review will pass on first read.

Customer + employee onboarding flows

AI-assisted onboarding (customer or internal) that pulls the right data, surfaces missing pieces, escalates clean issues to humans. Cuts onboarding cycle in half without cutting headcount.

BI-grade telemetry on AI usage

Which features get used, by whom, with what outcome. The reporting layer your CFO will ask for before greenlighting the next phase.

// the constraints we build around

Built knowing what your compliance team will ask.

SOC 2 Type II Posture

We deploy in patterns that fit your existing SOC 2 control framework — no exceptions, no carve-outs.

Private Models / BYOK

Closed-loop AI deployments. No external data flow. Customer-managed encryption keys where required.

GDPR / CCPA

Consent management, data residency, right-to-delete workflows built into intake and nurture by default.

HIPAA / PHI

For healthcare divisions — BAA-eligible deployments with audit trails and PHI segregation.

Internal Audit

Every system we build is documented for internal audit on day one. No 'we'll get to that later.'

Change Management

We ship inside your release cadence — CAB approvals, change windows, rollback plans — not against it.

// faq

Things enterprise operators ask first.

We have an internal AI team — why bring in an outside partner?

Your team operates against multiple priorities and a backlog. We come in narrowly, ship the production system, document it, and hand it to your team to own. We multiply your team, we don't replace them.

Can you sign our security review / DPA / MSA?

Yes. We've signed enterprise MSAs, BAAs, DPAs, and security review packets. We have the documentation ready. We won't slow your procurement team down.

Who actually owns what we build?

You do. Code, prompts, evals, pipelines — delivered in your repo under your infrastructure. Our retainer is for evolution and second-line support, not lock-in.

What's a realistic enterprise engagement size?

Phase 1 (one narrow production slice) is typically 8–12 weeks. After that, multi-quarter expansion engagements are normal. We don't sell the big slide deck upfront — we earn the second quarter with the first.

You've piloted enough.
Let's ship one to production.