Pioneers in
Context Engineering
Give AI the context it needs to perform like a top agent
Most AI projects fail for one simple reason: they try to “dump” existing knowledge into a model and hope it figures it out. In practice, that approach is unreliable and slow to fix.
Context Engineering is the work of transforming messy operational knowledge into clear, scenario-based instructions that AI can actually execute. It’s not just content cleanup. It’s building the operational “brain” that makes automation consistent, brand-safe, and scalable.
What is Context Engineering?
Context Engineering is the process of gathering the right operational materials (not everything, only what’s relevant), structuring them into scenario-specific instructions, and then feeding those instructions into the AI in a format it can follow reliably so it can route to the right scenario, follow steps in order, and perform consistently in real customer interactions.
Tech companies often receive whatever data exists and try to fit it into the AI. We go further: we help control and improve the collection, structure, and correctness of the inputs, so the AI performs better today not “in a few months”.
When AI DOESN'T have the right context
When AI DOES have the right context
What it looks like: Context Capsules
Our primary output is a set of structured, scenario-specific documents we call Context Capsules — each one contains everything the AI needs to complete a single scenario correctly, end to end.
Think of Context Capsules as a new kind of knowledge base: designed for AI execution, not just human reference.
They’re built to be actionable, not just informative, and each capsule includes:
Trigger + Goal
Step-by-step instructions
System + integration mapping
Brand voice enforcement
Decision logic
A new org structure
Traditional BPOs sell seats. Software vendors sell licenses. XO gets paid to deliver outcomes, which is why we restructured our org.
Teams aren’t adjacent to XOOS, they’re built into it
XOOS turns every department into an on-demand AI enablement team, so the right expertise shows up exactly when it’s needed: solutioning, context engineering, QA, and ongoing maintenance. No weeks-later handoffs.
What our approach of Context Engineering provides
Context Engineering is what turns AI from “interesting” into “operational.”It takes your team’s expertise, what your best people already know, and turns it into structured, actionable intelligence that AI agents can follow, so automation becomes consistent, reliable, and scalable.
Knowledge flows where it's needed
Your team's expertise becomes the foundation for intelligent automation. Context Engineering captures what your people know and transforms it into actionable intelligence for AI agents.
Automation that understands your business
AI agents work better when they understand the nuances of your operations. We embed domain knowledge directly into XOOS so every decision carries the weight of your experience.
Higher accuracy
Your operators know what matters most. We capture that knowledge into scenario-specific instructions, so AI agents act smarter and respond more accurately.
Consistent brand voice
Because the right language examples are enforced at the right steps
Faster implementation
because you’re not guessing behavior, you’re implementing documented logic (and you control the inputs)
Easier scaling
Because structured scenarios make it simpler to expand coverage and automate more volume over time
Want to see how this would work in your operation?
Book a demo to walk through your use case, or reach out to our team with questions.