What We Do
Four pillars. Each one delivered by people who’ve done it before.
No 40-vertical sprawl. Four things we’re actually good at — explained in the language of the people who’ll have to operate what we deliver.
Custom agents and MCP servers wired to your real systems
Agentic AI
We build production-grade agents that do real work — not demos.
We help you with
- →Multi-step agents that read, decide, and act across your tools
- →MCP servers exposing your internal systems to any LLM client
- →Eval harnesses so you measure quality, not vibes
What this looks like
- ·A vertically-focused operations agent that replaced four SaaS integrations
- ·An internal documentation agent grounded in private Git repos
- ·A research-and-summarize agent for an executive team
AIOps for the people who actually run the network
AI for Network & Data Center Ops
We turn telemetry into decisions, not dashboards.
We help you with
- →Closed-loop automation against your existing Cisco / vendor stack
- →Anomaly detection grounded in real config and flow data
- →Runbook agents that triage L1/L2 before a human pages
What this looks like
- ·A data-center topology assistant grounded in live config snapshots
- ·A capacity-planning model fed from streaming telemetry
- ·A change-risk classifier wired to ServiceNow change records
Practical AI for fitness, retail, and services SMBs
AI for SMB Operations
AI that saves your front-line staff time, not a chatbot for your homepage.
We help you with
- →Campaign and outreach automation that respects your brand voice
- →CRM, scheduling, and POS integrations stitched into one workflow
- →LMS / training audits and remediation for franchise networks
What this looks like
- ·Multi-location email campaign automation for a fitness franchise
- ·An LMS audit and remediation plan for a national training program
- ·A back-office reconciliation agent for a multi-vendor retailer
Pragmatic AI strategy without the McKinsey deck
AI Strategy & Advisory
A short, technical engagement that ends with a decision, not a roadmap.
We help you with
- →AI readiness assessments grounded in your real systems
- →Build-vs-buy and vendor-selection guidance with skin in the game
- →Fractional-CTO support for AI-adjacent product decisions
What this looks like
- ·A 30-day AI readiness assessment for a mid-market services firm
- ·Build-vs-buy guidance for a regulated-data use case
- ·Ongoing fractional-CTO support for an AI-first startup
How We Engage
Discovery → Pilot → Scale.
Every engagement starts with a tightly scoped discovery: we review your real systems and write a short memo that names the problem and proposes a pilot. Pilots are time-boxed and outcome-defined. Only after a successful pilot do we discuss scale.
Partner firms engage under our Master Collaboration Agreement — Prime/Sub, Teaming, or referral, with per-deal Schedules that name roles, scope, and economics.