Eight services. One engagement model.
Every engagement starts with an AI Systems Audit. After that we run the service with the same discipline we run our own production systems. Fixed-fee where we can; transparent where we can’t.
AI Solutions
Custom AI built into the spots where it genuinely changes what the business can do.
Too much AI today is closer to theater than infrastructure — chatbots that stall at ticket close, copilots that can't ship code. What we build does the end-to-end work: classifies inputs, makes the decision, runs the action, reports back. And we stay on the hook when it breaks.
Discovery — identify the few places AI would produce measurable ROI for your specific business
Architecture doc — models, data flow, failure modes, cost envelope
Build — every checkpoint ships to production as we go
Eval harness — so you can trust outputs before they affect revenue
Continuous monitoring — model drift, prompt regressions, cost overruns, live alerting
Scoping starts the week we sign. Build cycles ship in days per checkpoint and go to production as they land. Fixed-fee for engagements with clear scope, transparent hourly where the scope is still forming.
Workflow Automation
Turn repetitive work — ops, support, scheduling, reporting — into reliable, observable systems.
The boring work that consumes payroll and breaks silently. We replace it with systems you can actually see into and edit, rather than black-box no-code flows that fall over on the first edge case.
Process map — where time is actually lost (we watch, we don't guess)
Integration — connect the tools you already pay for
Guardrails — approval gates, rollback, rate limits
Continuous monitoring — you hear from us before your team does
Handoff — runbooks your team can operate
First workflow mapped in the opening week. Individual automations typically ship in days. Retainer optional for ongoing ops.
Ops Intelligence
Command-center dashboards that show cost, delay, failure, and throughput at a glance.
You can't fix what you can't see. Most dashboards are pretty charts of the wrong metrics. We design the metrics that actually move decisions for your business — and build the pipeline that keeps them honest.
Metrics model — the numbers that matter for your specific business, no templates. Sometimes that's three; sometimes it's a dozen.
Data pipeline — from tools → warehouse → live views
Dashboards — real-time, mobile-friendly, alert-capable
Alerting — on thresholds, on anomalies, on silence
Continuous monitoring — hourly by default, per-minute where stakes require it. You hear from us when something needs a decision.
Initial dashboards live within a week of data access. Monthly retainer optional as metrics evolve with the business.
GEO Consulting
Generative-engine optimization. Make your business legible to AI search, not just Google.
Search is splitting. Classic SEO still matters, but AI-native surfaces (ChatGPT, Perplexity, Claude, Gemini answers) are how a growing share of buyers now discover and qualify vendors. GEO is deliberate positioning inside those surfaces.
Audit — how you currently appear (or don't) across LLM surfaces
Content model — structure, facts, and citations AI engines actually ingest
Technical markup — schema.org, llms.txt, citation-friendly formats
Distribution — where content needs to live for engines to pick it up
Measurement — monthly visibility tracking across major engines
Audit delivered within days of site access. Month-by-month thereafter — results compound at 60–90 days.
Personalized Comms
AI-personalized messaging that sounds like a person, grounded in your CRM and brand voice.
Mass-personalization usually reads as mass-spam with first names. We build systems that condition on what's actually known — stage, tools, recent behavior, relationship — and send fewer, better messages.
Voice training — from your existing best messages, not a brand-guideline doc
Conditioning model — what data drives which variants
Templates — not rigid; structural with latitude
Send infrastructure — deliverability, warmup, suppression
Human review loop — sample-and-approve until trust is earned
Voice training starts on the first call. First sends go out in under a week. Volume-based retainer — we price against blended reply rate, not sends.
Production Hardening
For solo builders shipping AI apps — we pair on the gap between prototype and production.
You shipped an MVP. It works on your machine. Now it needs to survive real users, actual money, and the edge cases that MVPs don't cover. We plug in as a senior pair — reviewing the code, rebuilding the fragile parts, and adding the observability you haven't had time for.
Architecture review — what breaks at 10x, 100x
Observability — logs, traces, error tracking, SLOs
CI/CD — deploys you can trust and a rollback path you've actually rehearsed
Security — secrets, permissions, auth paths
Incident playbook — so the 2am page is actionable
Architecture review delivered in days. Hardening ships per-item as we go, not batched into milestones. Continues as needed.
AI-Native Web
Marketing sites and web apps designed for the AI era — built fast, instrumented from day one, with genuine AI capability where the site needs it.
A 2026 website shouldn't feel like a 2019 brochure. We build sites and apps that are fast, intentionally designed, AI-assisted to ship, and often AI-powered where it genuinely helps — chat, search, personalization, content ops. Our own site is an example. So is the one we recently built for a client, which outperforms this one on the benchmarks that matter.
Strategy — positioning, information architecture, what the site has to do
Design — on-brand and system-driven, so it doesn't read like another generic template
Build — performant, accessible, SEO + GEO ready
AI features where they pull their weight — things like chat, semantic search, personalization
Analytics + observability — you actually know what's working
Design system locked in the first week. Marketing sites go live within weeks; web apps scoped per engagement.
AI Evaluation & Safety
Independent review of AI systems before — and after — they make real decisions.
As AI gets permissions to act on real systems, someone has to answer whether it's safe to let it. That's rarely the team that built it. We audit your eval harnesses, red-team your prompts and agents, design permission boundaries, and write the incident playbook you hope you never need. Informed by operating our own agentic systems daily.
Eval audit — is your system being measured on what actually matters
Red-team — adversarial prompting, permission escape, jailbreak resistance
Permission model — the scope the agent can act inside, where it has to ask first, and what's off-limits entirely
Monitoring plan — what to log, what to alert on, what to review
Incident playbook — rehearsed response for when AI behavior goes sideways
Scope finalized on the kickoff call. Initial audits complete in under a week. Ongoing monitoring retainer optional.
Not sure which service fits?
That’s what the Audit is for. We look at your operations and tell you — honestly — which (if any) of these would actually move the needle.
Request an Audit