The hardest part of deploying an AI workforce is building the organization around it.
Notenic Services helps enterprises move from pilots to governed, repeatable workflows by hardening your deployment stack, designing enforceable controls, and establishing operational ownership across IT, Compliance, and Operations.
Every engagement is delivered by the team that designed the runtime. Direct practitioner access, from the first conversation to production handoff.
We accelerate platform adoption by delivering the implementation patterns, governance design, and production discipline required to run agents like a workforce with authority, accountability, and operational precision.
From assessment to operational in 90 days.
A structured sequence with defined deliverables, defined exits, and a clear handoff at each phase boundary.Days 1-30
Readiness & ArchitectureWorkflow and tool-surface mapping + Risk classification and autonomy tiering + Governance blueprint: roles, controls, escalation paths + Prioritised rollout plan.
Days 30-75
Build & DeployFlagship workflow implementation with governance bindings + Runtime enforcement and posture evidence + Observability, runbooks, and release process + Dev, staging, production.
Days 60-90
Scale & OperateOwnership enablement across departments + Expansion backlog and patterns library + Governance KPI framework + Executive and audit reporting model.
Days 90+
Continuous Hardening RetainerAs your agent fleet and operating environment evolves, governance must evolve with it. New workflows scoped, new policies authored - governance that stays ahead of deployment, not behind it.
Five engagements.
One production-ready outcome.
Each engagement is a defined-scope delivery with concrete deliverables and a clear production objective. They can be taken individually or sequenced as part of the 90-Day Launch Program.
Agentic Readiness Assessment
Establish what is safe to automate, where risk lives, and what must be governed — before a single agent reaches production.
- Workflow and tool-surface mapping (systems of record, APIs, egress)
- Risk classification + autonomy tiering (where to supervise vs automate)
- Governance blueprint: roles, controls, escalation paths
- Implementation plan + success criteria
- Readiness report
- Target architecture
- Governance control model
- Prioritised rollout plan
3–5 workflows identified and cleared for governed production deployment, with a prioritised sequencing plan for each.
Control Plane & Policy Architecture Design
Design the rules of work so governance is enforceable and portable — not locked in a document nobody reads.
- Role definitions and authority envelopes
- AI-PAM tool access design (least privilege for agents)
- Execution path controls: required steps, state machine
- NRPEP-style precedence and conflict resolution model
- Versioning, approvals, and release strategy
- Policy framework + control taxonomy
- Approval/rollout workflow
- Initial governance artifact set
A complete, versioned control plane ready for deployment — governance that can be enforced the day the first workflow goes live.
Production Hardening & Runtime Integration
Integrate Notenic into your stack with performance, reliability, and audit evidence in mind, from the first day in production.
- Integration pattern selection: entrypoint vs sidecar vs control-plane only
- Runtime deployment in your boundary (cloud/on-prem/edge)
- Logging, telemetry posture, and audit evidence strategy
- Resilience patterns: fallback, retries, safe-mode, escalation
- Performance tuning: latency, throughput, cost controls
- Deployment guide + hardened runtime configuration
- Observability plan
- Production runbooks
A hardened, observable production runtime — with governance evidence generation active from session one.
Use-Case Implementation Sprints
Governed workflows that work. Choose your domain (SecOps, ITOps, or FinanceOps) and we deliver production-ready workflows with controls, patterns, and operational handoff.
- SecOps: supervised remediation, containment runbooks, controlled egress
- ITOps: incident triage, change validation, safe-action boundaries
- FinanceOps: approvals, SoD constraints, thresholds, audit trails
- Working production workflows + governance bindings
- Test/eval results
- Operational handoff documentation
One or more domain workflows in governed production — with a standard pattern library for onboarding the next workflow independently.
Operating Model Enablement
Ensure adoption scales without turning into DevOps overload. Define who owns what, who supervises whom, and how governance evolves as the agent fleet grows.
- Ownership model by department (who publishes what controls)
- Manager profiles and supervisory roles
- Training for control owners: Security / IT / Finance / CoE
- Governance KPIs: posture, drift rates, escalation rates, exceptions
- Cadence: change control, audit readiness, continuous improvement
- RACI + governance playbook
- Training sessions
- KPI dashboard specification
A self-sustaining operating model where governance does not require Notenic to be in the room for every change — scalable across the full agent fleet.
Every function has a different definition of success. We deliver against all of them.
- Runtime-enforced controls at the execution path
- Audit-ready posture with turn-by-turn evidence
- Drift detection and injection resilience
- Hard stops, fallback modes, and escalation paths
- Patterns for sidecar, in-process, and adapter deployments
- Designed for sub-15ms performance in validated conditions
- Scalable governance without creating a DevOps admin burden
- Decentralized ownership model that reduces ops overhead
- Versioned controls with approvals and rollout audit trail
- Evidence packages aligned to SOC 2, ISO, HIPAA, GLBA, FFIEC
- Investigation-ready session posture records
- Separation-of-duties enforcement at the tool layer
- Standard patterns and reusable control libraries
- Extensible adoption model for new workflow onboarding
- Partner enablement kits for SI distribution
- Governance KPI framework for the full agent fleet
The team that architected the runtime is the team that builds your implementation.
Not a generalist consulting team that learned the Notenic platform from a training deck.
There is no handoff between the people who understand the architecture and the people who show up to your engagement. The same practitioners who designed the governance model, stress-tested the policy framework, and worked through the edge cases in production environments are the ones who will be in the room with your team. That continuity is not incidental — it is how we ensure that what we build with you actually holds up.
Ari Havenga
Architect of the Notenic AI runtime governance model and the K-coefficient cognitive governance framework. Ari brings a rare combination of deep technical design capability and operational leadership forged across business turnarounds, hyperautomation programs, and positive-sum automation deployments. His background in Six Sigma operations gives Notenic's governance architecture a discipline that most AI infrastructure companies do not carry — a commitment to measurable, repeatable outcomes over impressive-sounding claims.
Co-FounderMike Mendelsohn
Enterprise technology GTM leader with sustained quota outperformance across Oracle, ServiceNow, and Zendesk. Mike brings the distribution expertise and enterprise relationship depth that translates a category-defining product into a category-leading market position. He understands how regulated enterprises evaluate, procure, and adopt infrastructure software — and how to remove the organizational friction that keeps the right technology from reaching the people who need it.
Choose your entry point.
Embed governed autonomy in your delivery practice.
If you are a system integrator or technology partner delivering agentic AI implementations to enterprise clients, the Notenic partner track gives your delivery team the platform access, reference architectures, and enablement materials to govern those deployments from the first sprint.
Partners require a runtime governance layer that works reliably inside the environments they are already deploying into, with a team that can support the hard technical and organizational questions when they arise.