A demonstration is not an operating system.
Production value requires integration, evaluation, exception handling, security, ownership and maintenance.
Applied AI, software & intelligent systems
Turn high-friction workflows into governed intelligent systems.
PlanckCyber helps organizations define the right problem, prove the workflow, build the production system, and operate it with measurable controls.
A senior working session for organizations with an accountable sponsor, a defined workflow, and a decision to make.
Workflow signal
Readiness: 68%
Sponsor and data access confirmed. Evaluation baseline required.
Human approval required
Material actions remain governed.
Outcome-first scopingBegin with the operating result, not a model.
Human control by designDefine authority, approvals and exceptions.
Measurable acceptanceEstablish baselines and thresholds before claims.
Senior accessDirect working sessions with accountable experts.
Primary value proposition
Move from AI possibility to operating performance.
The technology is only one part of the system. Production value depends on workflow design, data, integration, evaluation, security, ownership and controlled change.
PlanckCyber combines strategy, software engineering and operating discipline so clients can make a defensible decision before scaling.
The problem
AI projects stall when the workflow, evidence, ownership and controls are undefined.
Most implementation risk is not hidden inside the model. It sits in the surrounding operating system.
A model choice is not a business decision.
The correct system depends on the workflow, data, risk, cost and acceptance method.
Autonomy is not the default.
Material actions and uncertain exceptions require explicit human authority and auditability.
Value must be measured.
Cycle time, quality, adoption, cost and risk need baselines before claims can be made.
Core services
Use the smallest engagement that creates a defensible decision.
The commercial path reduces risk before a large production commitment and creates a clear expansion path when evidence supports it.
01
AI Opportunity & Readiness Sprint
Prioritize workflows, establish baselines, identify data and control dependencies, and produce an executable roadmap.
- Use-case ranking
- Data and integration review
- Risk and control plan
- Decision-ready roadmap
02
Workflow Automation Pilot
Test business value, technical feasibility, security, adoption and operating ownership in a bounded environment.
- Production-relevant workflow
- Evaluation baseline
- Human-control design
- Go / no-go decision
03
Production Intelligent System
Engineer the application, integrations, retrieval, agent controls, evaluation and monitoring required for production use.
- Application and integration
- RAG and agent architecture
- Security and observability
- Deployment and acceptance
04
Managed AI Operations
Monitor quality, incidents, usage, cost, model changes and controlled improvements after deployment.
- Evaluation monitoring
- Incident and change control
- Cost and usage review
- Managed expansion
Commercial note: Engagement scope and pricing are confirmed after qualification. Planning ranges are not guarantees or quotes.
How the process works
Define. Prove. Build. Operate.
Each phase has a decision, an accountable owner and an acceptance standard.
Define the outcome
Bound the workflow, sponsor, baseline, users, data and decision deadline.
Output: decision frame
Prove the workflow
Test value, feasibility, controls, adoption and ownership before scaling.
Output: go / no-go evidence
Build the system
Integrate real tools and data with evaluation, security and human control.
Output: production capability
Measure and improve
Monitor quality, incidents, cost and controlled change after deployment.
Output: managed performance
Customer and use-case fit
Start with work that is frequent, measurable and governable.
The strongest starting points have a clear owner, accessible inputs, repeatable decisions and a way to evaluate quality before production.
Best-fit conditions
- Accountable executive sponsor
- Defined workflow and user group
- Accessible systems and data
- Measurable baseline and decision date
Document and review
Triage, extraction, drafting, comparison and human-review workflows.
Knowledge operations
Retrieval, synthesis, evidence tracing and expert escalation.
Customer operations
Assisted service, routing, response preparation and quality monitoring.
Planning and analysis
Research, scenario preparation, reporting and decision support.
Why PlanckCyber
Senior engineering judgment without legacy-consulting distance.
Systems over symptoms
We solve for the connected operating system, not an isolated demo or prompt.
Rigor over hype
We distinguish what can be built, measured and governed from what is merely fashionable.
Outcomes over output
The work is complete when it changes performance under agreed acceptance criteria.
Advanced but understandable
Clients should understand what is being built, why it matters and how it is controlled.
Practical partnership
Senior access, transparent decisions and direct accountability throughout the engagement.
Progress through feedback
Evaluation, monitoring and controlled change are designed into the system from the start.
Governance and security
Understandable architecture. Explicit controls. Observable performance.
- Documented data flows, permissions and model dependencies
- Human approval for material actions and uncertain exceptions
- Evaluation sets, acceptance thresholds and regression testing
- Logging, monitoring, incident triage and controlled change
- Clear client ownership, responsibilities and transition plans
1Business outcomeBaseline, owner, acceptance
2Human authorityApprovals, exceptions, escalation
3System controlsPermissions, evaluations, logging
4Model and dataProviders, retrieval, retention
Evidence before claims
Proof will be earned, documented and permissioned.
PlanckCyber is a startup. Credibility will be built through verified credentials, working demonstrations, evaluation artifacts and client evidence that may legally be disclosed.
Verified founder credentialsPending final public verification
Working demonstrationsBuilt around representative workflows
Evaluation artifactsBaselines, thresholds and regression results
Permissioned case evidencePublished only with written authorization
0Invented client logos or testimonials
100%Claims subject to evidence
Decision resource
Which workflow should you evaluate first?
Use the AI Workflow Candidate Scorecard to compare value, measurability, feasibility, control requirements and operating ownership.
The scorecard is educational. Results require human review and do not guarantee feasibility, return on investment or approval.
AI Workflow Candidate ScorecardIllustrative
Business value4.2
Data readiness3.6
Control fit4.5
Ownership3.2
Recommended next stepDefine an evaluation baseline before pilot approval.
Practical resources
Make better implementation decisions before committing capital.
Each resource is designed to help a buyer clarify the workflow, evidence, controls or commercial decision.
How to scope an AI workflow pilot
Define the workflow, baseline, evaluation, user group and stop conditions.
Read the guide →AI agent control matrix
Map tools, permissions, approvals, exceptions, logs and escalation.
View the framework →Build, buy or integrate?
Compare ownership, differentiation, integration, security and lifecycle cost.
Compare options →Frequently asked questions
Direct answers before a working session.
PlanckCyber is selective about workflow fit, governance and readiness. Not every AI idea should become a project.
What makes a workflow suitable for AI?
The work should be frequent enough to matter, bounded enough to evaluate, supported by accessible data, owned by an accountable sponsor and governable with clear human controls.
Do you build autonomous agents?
PlanckCyber can engineer agentic workflows, but autonomy is bounded by permissions, risk, observability and human authority. High-impact autonomous decisions are excluded from the initial service scope.
Can you work inside our cloud and security standards?
That is the preferred production model when feasible. Architecture, access, data handling and provider choices are defined during readiness and security review.
How do engagements begin?
Qualified opportunities begin with a brief senior working session and usually progress to a fixed-scope readiness sprint.
Do you guarantee ROI or performance?
No. PlanckCyber defines measurable acceptance criteria and evaluates results, but does not guarantee savings, revenue, accuracy, security or regulatory outcomes.
Next decision
Bring one workflow, one sponsor and one decision deadline.
We will determine whether a readiness sprint, a relevant resource, or no engagement is the right next step.
Request a workflow briefing
Contact PlanckCyber
No obligation. No automatic qualification. Senior review required.