Thirty-five years in managed services. Software in production. A small number of serious engagements.
Codedaptive is the consulting and software practice of Bob and Amelia Pankratz.
The work comes out of a nineteen-year MSP run through strategic acquisition, an active vCISO practice, advisory roles across core industry platforms, and production software serving paying customers today.
The consulting sits where managed services operations meet the AI capabilities now reshaping the industry. We work with MSPs preparing to grow, acquire, or sell. We advise vendors that need senior operator perspective on product direction. We help operators separate what AI actually changes from what the industry is only pretending has changed.
We take on a small number of engagements at a time because this work requires context, judgment, and direct involvement. Volume is not the model.
Bob founded TechNosis in 2005 and ran it for nineteen years as a fully remote managed services firm, growing it to a fifteen-person team before completing a strategic acquisition in December 2024. Across that run: zero client security breaches, zero unrecoverable data-loss events.
Earlier, he led worldwide IT at Plexus Corp through acquisition-driven growth, integrating six IT departments across fourteen global locations. He has served on product advisory councils for Kaseya, Autotask, and Datto. He holds a B.S. in Mathematics from Stetson University and has been building systems since neural networks were still mostly an academic curiosity.
His specialty is structural design: how technology, people, and process are assembled into operations that work at scale. The production agentic systems he deploys in client environments run on a substrate he designed and built himself. The problems that find him usually require someone who can design the system and has also run the business.
Amelia spent seven years at TechNosis, rising to Director of Operations before the acquisition. Since then she has run vCISO engagements for MSPs and mid-market clients, built governance frameworks aligned to NIST, CMMC, and cyber-insurance requirements, and led organizations through compliance programs from the ground up.
She also ships software. ClarityCalc, her production SaaS platform for MSP pricing and profitability analysis, serves paying customers today. She built it with the discipline security practitioners develop: tenant isolation by default, audit trails on consequential actions, and no deployment without a review gate.
Her work sits in the overlap between automation and governance. She designs workflows that remove manual overhead from operations, and compliance frameworks that make those workflows auditable and defensible. MSPs that have grown past what the founder can hold in their head generally need both.
Bob designs the operating structure: how technology, people, process, and accountability fit together into something that scales. Amelia builds the automation and governance layer: the workflows, controls, and documentation that make the structure repeatable and defensible. PSA and RMM are shared ground. So is the expectation that the work gets done.
Where agentic AI belongs in service delivery today. Ticket triage and routing, documentation generation, customer communication, and the governance model that keeps humans accountable for machine-assisted work. We have deployed these workflows in production environments and know where they break.
Most MSPs run on manual workflows embedded in tribal knowledge. Amelia designs the automation layer: the processes that move without human intervention, the exception handling that escalates correctly, and the documentation that makes the system auditable. The goal is an operation that runs the same way whether the founder is in the room or not.
Metrics that tell you whether service delivery is working: SLA performance, ticket aging, technician utilization, recurring revenue per seat, agreement profitability, and the gap between what the PSA says and what the business is actually doing. Built where the team can act on them and framed in terms clients can understand.
How a ticket moves from intake to resolution. Triage rules, assignment logic, escalation triggers, communication standards, and the documentation practices that make the work defensible. Built once, enforced consistently.
Autotask treated as an operating system, not an administrative database. Account structures, contract frameworks, service desk workflow, billing configuration, and accounting integration. Most MSPs inherited a PSA configured by whoever was available when the system had to go live. We rebuild it as deliberate operational infrastructure.
Policy libraries, monitoring templates, automation rules, and alert tiers designed for managed services at scale. The difference between an RMM that creates noise and one that surfaces signal is almost always configuration, governance, and restraint.
Contract language for the current moment in the industry. Scope definitions that do not create service debt. The frameworks Bob developed at TechNosis were adopted by roughly a dozen MSPs across North America as the basis for their own client contracting. Amelia's governance lens makes sure the same structures can survive cyber-insurance review and compliance scrutiny.
Codedaptive works with a small number of engagements at a time. If the work described here intersects with a problem you are working on, reach us directly.
ClarityCalc gives managed services providers the financial visibility their pricing decisions require. Build a service catalog with tool and labor costs attached, calculate margin by client and service bundle, generate client-facing statements of work, and understand why each engagement costs what it costs.
The platform is multi-tenant and Stripe-billed, with the governance posture expected by organizations operating in regulated environments. Features include plan lifecycle management, discount guardrails with margin-health thresholds, SOW document generation, and self-service signup with tiered feature entitlement.
ClarityCalc is in production today, serving paying customers.
MOOTx01 is the long-term memory layer for AI that the platforms have not shipped. It runs on-device, under the user's control, and exposes its interface through ARIA, an open specification any AI client can adopt. The intelligence is rented. The memory is owned.
The substrate covers the stack from math primitives through spatial memory, vector search, knowledge graph, RAG bundles, and a dreaming daemon that consolidates memory while the device is idle. Swift and Rust implementations are conformance-gated against shared test vectors.
For vendor partnerships, Apple platform licensing, SDK integrations, and commercial edition inquiries, reach us directly.