Otonmi is an AI implementation firm. We enter operational environments, deconstruct workflows, and deploy AI systems that reduce human dependency in specific, measurable ways.
Structured execution.
Reduced human dependency.
We are not consultants. We don't produce strategy documents, implementation roadmaps, or AI readiness assessments. We enter your operational environment and build systems that work.
The distinction matters. Most organizations don't have an AI strategy problem. They have an execution problem: a gap between knowing AI could transform a workflow and having a working system that actually does it.
That gap is what we close.
We work with organizations that have a specific operational problem and the organizational maturity to act on a solution. Three profiles consistently appear.
COOs, VPs of Operations, and Directors of Operations who own the workflows and know where the bottlenecks are, what's breaking, and what would change if specific processes ran without constant human intervention.
// operational authority
CTOs and VPs of Technology who understand AI's potential and have the technical mandate to deploy it, but need structured methodology to ensure what gets built actually reduces operational burden rather than creating new complexity.
// technical mandate
CEOs and founders who have identified a specific operational constraint and need it resolved, not studied. Often in growth contexts where operational capacity hasn't scaled with commercial growth.
// execution authority
Otonmi is a DBA of Ingress IT Solutions. Our leadership brings deep federal IT experience, AI implementation expertise, and hands-on delivery backgrounds across government and enterprise environments.
Founder of Ingress IT Solutions and architect of the Otonmi AI implementation practice. Leads federal and enterprise AI engagements with a focus on structured execution and measurable operational outcomes.
LinkedInLeads Otonmi's delivery practice and client partnerships. Brings extensive experience in digital transformation, AI governance, and technology strategy across enterprise and public sector organizations.
LinkedInThe organizations that get the most from an AI Kaizen Event are past a specific threshold. They're not exploring whether AI is relevant. They're past that question.
They've watched competitors automate processes. They've seen case studies. They may have run pilots or PoCs. Some have already tried to implement AI and watched it stall in a proof-of-concept that never made it to production.
What they haven't done is close the execution gap - the distance between "we know AI can do this" and "we have a working system doing it." That's the specific problem we solve.
The organizations that aren't a fit are still exploring whether AI is relevant, not yet ready to commit a specific workflow for transformation, or looking for a low-risk pilot rather than a production outcome.
Signals you're ready
We'd rather tell you we're not the right engagement than waste your time and ours. Here's an honest read.
"If there isn't a clear engagement opportunity, we'll say so in the first conversation and tell you what would need to be true for one to exist."
We don't run a sales process. We run a direct conversation about your operational reality. If the workflow you're describing doesn't have the characteristics that make an AI Kaizen Event viable (vague problem, undocumented workflow, insufficient organizational readiness), we'll tell you that.
We'd rather have a 30-minute conversation that ends with "not now, here's why" than run a multi-week engagement that doesn't produce a system that works. Our entire model depends on engagements that succeed.
If the engagement is right, we'll define a starting workflow, propose a scope, and tell you what success looks like before we begin.
Tell us about your operation. We'll assess whether there's a viable engagement and be direct about our read, in both directions.