Applied AI · Software · Intelligent Systems
PlanckCyber helps companies identify high-value AI opportunities, automate workflows, build custom AI applications and agents, and operate intelligent systems securely.
What We Do
Start with a business problem, a defined technical need, or an existing AI system that needs improvement.
Service
Find the AI opportunities worth pursuing, define a practical roadmap, and make investment decisions with evidence rather than hype.
Service
Design AI agents and automated workflows that perform defined work, connect systems, and keep people in control where judgment matters.
Service
Build custom AI applications, copilots, internal tools and product features around the workflow, data and experience your business actually needs.
Service
Turn scattered documents and enterprise knowledge into searchable, usable systems for people, applications and AI agents.
Service
Operate, evaluate and improve AI systems after launch so quality, cost, security and business fit do not drift unnoticed.
AI Strategy & Consulting
PlanckCyber helps leaders identify high-value use cases, assess readiness, test feasibility, define measurable outcomes and create a practical path from strategy into proof and implementation.
Prove Before You Scale
Test model behavior, data, retrieval, integrations, workflow fit or controls before committing to a production build.
Explore AI Proof of ConceptWhat We Build
Software that interprets context and uses approved tools to complete bounded tasks.
Retrieval and search systems that make approved organizational knowledge usable.
Connected processes that reduce repetitive work and surface exceptions.
Purpose-built software, copilots and product features around your workflow.
Extraction, classification, comparison and review for document-heavy work.
Controlled connections between models, business applications, APIs and data.
Coordinated agents for complex workflows where evidence supports the added complexity.
Not Sure Where to Start?
Tell us where work is slow, expensive, repetitive or difficult to scale. We will help determine whether AI can meaningfully improve it — and what the next step should be.
Right-sized entry
A clearly defined problem can move directly toward proof or build. A broader opportunity can start with a focused workshop. An existing AI system can start with evaluation and repair.
Prove Before You Scale
Test the assumptions that matter — data access, model behavior, integration, workflow fit, user adoption and controls — before committing major capital.
Common Business Problems
Why PlanckCyber
Define the operating problem and outcome before selecting technology.
Prototype uncertain assumptions and measure acceptance before scaling.
Design for integration, evaluation, operations and change—not just a demo.
Treat permissions, sensitive data, reversibility and human authority as system requirements.
Keep decisions close to accountable senior expertise.
Select models and tools around the requirement rather than a fixed vendor narrative.
Demos & Evidence
Until permissioned client case studies exist, PlanckCyber uses clearly labeled demonstrations, reference architectures, evaluation artifacts and control methods rather than invented proof.
Representative workflow showing bounded actions, tool permissions and human escalation.
Representative evaluation method for retrieval relevance, grounded answers and failure analysis.
Reference architecture for intake, extraction, validation, review and downstream integration.
How we work
PlanckCyber pairs applied AI engineering with disciplined project execution — clear scope, measurable acceptance criteria and direct accountability from discovery through delivery.
See our approachBrand principle
PlanckCyber distinguishes what can be built and measured from what is merely fashionable.
Resources
A business-first method for turning workflow friction into a prioritized AI opportunity.
Read guideA buyer framework for comparing strategy, engineering depth, evidence and accountability.
Read guideA directional self-assessment for opportunity, data, systems and operating readiness.
Take assessmentSee all AI consulting resources
No. A specific problem is enough to start. PlanckCyber can help determine whether the next step should be strategy, a focused proof, a direct build or no AI investment at all.
No. The workshop is one discovery path for organizations that need prioritization. Defined problems can move directly toward proof or build, and existing systems can begin with evaluation.
Engagements are scoped around the opportunity, technical complexity, data and integration requirements, risk, timeline and business value rather than a universal public price.
Start with the problem
You do not need a specification. Tell us what you are trying to improve.