Applied AI · Software · Intelligent Systems
Reduce the work that slows your business down.
Build a business that responds faster, misses fewer opportunities, spends less time on manual administration and operates with clearer control. PlanckCyber turns costly operating friction into systems that keep working after the project ends.
Selected Work
See the systems behind the claims.
Real examples of business workflows PlanckCyber has turned into software, AI-assisted operations and controlled automation.
AI COO
A production AI operating layer that accepts plain-English requests, routes work to the least expensive capable model, connects to business systems, and pauses for human approval before risky or costly actions.
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Custom Agency CRM
A custom CRM for an agency that connects lead capture, tracked phone lines, pipeline management, automated follow-up, customer records, reporting, compliance controls and an after-hours AI receptionist.
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Apex Platform
A working platform that connects customer signup, AI-assisted website creation, domain registration, hosting, email delivery, billing, client access and day-to-day management.
View projectWhere value usually hides
Start with the friction you already feel.
You do not need an AI roadmap. A slow, expensive, repetitive or unreliable workflow is enough to start the conversation.
Good leads are being missed.
Calls go unanswered, follow-up depends on memory, or customer information lives in too many places.
Your team repeats the same work.
Employees re-enter information, prepare the same reports, chase documents or manually coordinate routine steps.
Growth requires adding people too quickly.
Volume increases, but the underlying workflow still depends on individual employees moving every task forward.
Important knowledge is hard to use.
Answers exist inside documents, systems and employees' heads, but finding the right information takes too long.
You cannot see what is really happening.
Pipeline, finances, operations or customer work are spread across systems that do not tell one coherent story.
You have an AI idea but not enough evidence.
Before making a larger investment, you need to know whether the workflow, data, economics and controls actually support it.
What gets better
The goal is not more AI. It is a better-running business.
Technology only matters when it improves how work gets done, how decisions get made, or how customers are served.
Move repeatable coordination, data entry, document handling and routine follow-up into reliable workflows.
Capture calls, requests and opportunities when they happen instead of waiting for someone to become available.
Bring important workflow, customer and performance information into systems leaders can actually use.
Encode follow-up, routing, approvals and controls into the system instead of depending on memory.
Let software handle repetitive volume while people focus on judgment, relationships and exceptions.
Use approvals, permissions, logs and read-only access where the business cannot afford uncontrolled actions.
Three ways to start
Begin from where your business actually is.
You know the problem
A workflow is clearly costing time, money or opportunities.
Start with the business problem. We can determine whether the right answer is automation, AI, custom software or a simpler change.
Discuss the problem →You know AI could help
You need to find the highest-value place to start.
Use the readiness assessment or a focused opportunity workshop to identify the strongest practical use case before committing to a build.
Assess an opportunity →You already have AI
The system exists, but you do not trust or like the results.
Evaluate quality, workflow fit, cost, controls and operating reliability before deciding whether to repair, expand or replace it.
Review the existing system →How the work moves
Prove what matters before you scale.
Increase investment only as the evidence improves. A well-defined problem can move faster; an uncertain one should be tested before a larger commitment.
Discover
Clarify the outcome, workflow, people, systems, data, constraints and cost of the current problem.
Prove
Test the assumptions most likely to make the system useful—or make the investment a mistake.
Build
Engineer the software, integrations, controls and user experience around the proven workflow.
Operate
Measure what happens in production, fix exceptions and expand only where the results justify it.
Built for accountable automation
The useful question is not "Can AI do this?" It is "Can the business trust the system to do it correctly?"
- Human approval where actions are consequential
- Role-based access to sensitive information
- Logs and audit trails for important actions
- Read-only access where systems must never move money or alter records
- Explicit handling of uncertainty instead of fabricated answers
Not ready for a sales conversation?
Evaluate one opportunity first.
Use the AI Readiness & Opportunity Assessment to test business fit, technical feasibility and operating readiness before deciding what to build.
Start with the problem
What is slow, expensive, repetitive or hard to scale?
You do not need a technical specification. Tell us what your team is trying to improve, and we can determine whether technology is the right next step.