About
Building automation systems
that get stronger over time
FenexisOps builds AI-powered automation for businesses that are tired of manual processes, broken scripts, and systems that need constant babysitting. We engineer pipelines that self-heal, compound reliability, and cost pennies to run.
By the numbers
The 3-Layer Architecture
Most AI automations fail because they try to do everything in one prompt. We separate concerns into three layers, so each part does what it does best.
- 1
Layer 1: Directives
Natural language SOPs that define the goal, inputs, tools, outputs, and edge cases. Written like instructions you would give a skilled employee. Clear, structured, complete. These live in version control and improve over time.
- 2
Layer 2: Orchestration
The AI sits here — reading directives, calling tools in the right order, handling errors, asking for clarification when needed. It is the glue between intent and execution. Decision-making, not data processing.
- 3
Layer 3: Execution
Deterministic Python scripts that handle API calls, data processing, and file operations. These are reliable, testable, and fast. No hallucination risk — just code that runs the same way every time.
Self-Annealing Systems
Traditional automations break and stay broken. Ours get stronger. When something fails, the system runs a self-improvement loop.
Detect and diagnose
The system reads the error message and stack trace, identifies the root cause, and determines whether it is a code issue, an API change, or an edge case.
Fix and test
The execution script is patched and tested automatically. If it uses paid APIs, the system flags it for human review first.
Update and strengthen
The directive is updated with what was learned — new API limits, timing constraints, edge cases. The system is now stronger than before the error.
Principles
The beliefs that shape how we build.
Deterministic over probabilistic
AI makes decisions. Code does the work. This separation means 95% of your system runs with 100% reliability.
Compound reliability
Every error makes the system stronger. Over weeks and months, automations become increasingly robust as edge cases get handled.
Cost efficiency by design
We use the smallest model that gets the job done, batch operations where possible, and cache aggressively. Most systems cost $1-5/month to run.
Want to work together?
Tell us about your business and we will show you what can be automated.