$100M+, top 30 MSP in US >90% lower cost
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Cloudflare
Microsoft 365
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Transform your business with AI that actually delivers ROI.
Custom AI systems that automate your high-value business workflows from the inside, end to end. Deployed inside the enterprise stack you already use, no migrations needed.
Selected results
See more $100M+, top 30 MSP in US Govt agency, oversees 7% of GDP
$300K saved yearly
Regulatory service operations
$100M+, top 30 MSP in US 10x faster
Support triage
Sheila built us an AI system that spotted a recurring client issue hiding in months of ticket data. She helps us see what in AI can actually create business value.
Sheila is a rare partner who goes beyond the statement of work to set us up for long-term success. She proactively spots opportunities we didn’t think to look for.
Why AI projects don't become business ROI.
Most AI projects don't move the bottom line. Here are the 3 places I usually see them break.
Your AI projects need a business filter.
Your AI problem is not a shortage of ideas or investment. It's funding use cases that never touch a workflow important enough to move the business.
I help you narrow the field to workflows with technical feasibility, usable data, and a clear path to ROI. The output is one highest-ROI workflow worth building first.
Your ROI happens in your workflows.
Most AI tools make one step faster: a summary, a draft, a recommendation. But your expensive work isn't one step. It's the chain of work that pulls your people into manual coordination.
If that chain doesn't change, isolated tasks get faster, but your workflow still gets stuck before and after them.
ROI shows up when the workflow itself changes — AI handles the repeatable work, humans stay in control of key decisions, and work actually moves differently.
Once the right workflow is chosen, I build it into a production AI agent system.
Built inside your existing stack.
For your workflows to change, AI cannot sit off to the side. Your agent systems need to be where your teams already work.
I integrate agent systems into your existing stack, so your people aren't left chasing work across tools.
Non-exhaustive examples
From AI opportunity to measurable ROI.
Most AI spend gets trapped in isolated productivity gains. I start with the workflow that can move the business, then deliver a live agent system running in your cloud within 8 weeks, with a dashboard showing the money it saved you.
Stage 1 2 weeks
Find where AI can create value for your business.
I start by narrowing the field. Each candidate workflow is scored for business value, repeatability, data readiness, risk, and production complexity.
Not every workflow is worth automating. I find ones with high return and high feasibility that can deliver strong ROI.
Stage 2 2 weeks
Redesign your workflow around AI.
I map how the workflow actually runs across your teams and systems. Then I redesign the process and build the AI agent system to handle it.
LLM choice comes after the workflow is clear. I'm provider-agnostic, choosing the LLM and deployment path that fits your privacy, latency, and cost needs.
Workflow: Invoice Exception
Today: Manual
Redesigned with AI agents
Read & match invoice
By hand, one invoice at a time
Look up the policy
Spreadsheet, tribal knowledge
Chase an approval
Email back-and-forth
Key into ERP system
Re-typing, human error
3 days: Manual, error-prone
Read, assess, routeAI
Many invoices processed in parallel
Applies your policy RETRIEVAL
Deterministic, auditable
Approves exceptions HUMAN
Only when needed
Posts to ERP systemAI
NetSuite · SAP · CRM
Monitored & logged TRACING
Exceptions reviewed
Minutes: Automated, logged
Stage 3 1 week
Ship it live, on your cloud.
I deploy the agent system on your cloud, with monitoring, human approvals, and documentation. Your team can trust and operate it from day one.
Your infrastructure, your data, your control. The entire system runs inside your environment.
AWS 
Azure 
Google Cloud Stage 4 3 weeks
Measure and optimize.
After launch, I quantitatively track agent performance and improve it with structured evaluation loops.
I don't just hand you an agent and walk away. I stay until it pays off.
Live agent performance – Week 20
Value delivered since launch
$584K
Staff hours freed
312 hrs
Agent accuracy
98%
ROI since launch
Next step
Before another AI project starts
Make sure there's a path to business ROI. Find out how your operational workflows can be turned into cost savings.
Built for enterprise trust.
Every implementation is designed around the controls you need before AI touches live work.
Your data is protected by design — what reaches the LLM, what is stored where, who sees each part of your workflow.
I define these boundaries with you upfront, then enforce them on every run.
Access stays scoped. Agents reach your systems through bounded integrations, not open-ended data access.
They see only the records the workflow requires.
- Data permissions mapped to your business roles
- Boundaries inherited from your identity provider
Action Limit Policy
CRM — Update deal stage Deals under $25k value allow
Billing — Issue refund Up to $1k allow
HR — Read employee salary deny
Humans stay in control. High-risk decisions route through your approval chain first.
The agent prepares the action. Your team decides whether it executes, and nothing happens until human approvals clear.
01 Draft action auto
02 Risk classify auto
03 Awaiting your team's approval hold
04 Execute on approve
Every agent step is traced — inputs, reasoning, actions, escalations, and outcomes.
All logged so your team can inspect what happened and why.
- Replayable, queryable, exportable
10:42:07inputRefund request — $1,800
10:42:07reasonMatches refund policy 4.3 — Eligible
10:42:08tool callStripe — Issue refund
10:42:09escalateAmount over $1,500 — Routed to Operations
10:42:34approveMark Smith
10:42:34actionRefund issued
Agent behavior is evaluated continuously.
Regressions surface in testing, before they ever reach users.
Evaluation suite Coverage Result
Expected responses 98%
Edge cases 95%
Expert-reviewed set 99%
Re-run continuously, before & after launch
Failures have a path. Uncertain outputs, edge cases, and errors route to fallback paths instead of silently breaking.
- Confidence thresholds defined per action
- Edge cases go to the right human
- Errors trigger predefined recovery rules
Results delivered.
Enterprise workflows automated
Enterprise data intelligence
Minutes Time to insight
AI data agent built over core enterprise system that answers data questions and takes actions.
Days → On-demand
Complex data analysis Manual → Natural language query
Analysis mode Self-checks, self-corrects, self-improves
Autonomous reasoning "Sheila built us an agent that understands how our business works and that goes beyond data lookups to deliver analysis that’s useful for our strategic decisions. She also spotted multiple opportunities we hadn't thought to look for. She's a rare partner who goes beyond the statement of work to set us up for long-term success."
Steve Banke CTO
Client churn intelligence
>90% Cost reduction
Agent autonomously monitors scattered and high-volume risk signals in the background, flagging at-risk clients to account managers proactively.
$250K → $500
Annual cost Prohibitively manual → Automated
Feasibility "Analyzing client churn risk has always been brutally manual for us, as it was hard to keep close tabs on many clients or risk signals. Sheila turned that into an AI system that surfaces repeated patterns over time, making churn risk visible in a way we couldn't do before. Within weeks, it flagged a client issue that had been hiding in our ticket data for months."
Ted Brown Director
Government Agency Oversees 7% of GDP
Regulatory service operations
$300K Annual labor cost saved
5figures Cases automated
Frontline service operations automated end-to-end across document intake, data verification, and case resolution.
Every case → Exception only
Manual intervention 30% → 99%
AI workflow accuracy 3 days → Minutes
Service turnaround 
Ntiva, Inc. $100M+, top 30 MSP in US Support triage
10x Faster
3x Accuracy
Triage rebuilt into standardized AI decision flow, reducing review friction and making prioritization consistent at scale.
Minutes → Seconds
Triage time per ticket Reviewer-dependent → Standardized
Priority logic "We had a hard time getting our specific triage process into a working AI system. Sheila got us there."
Steve Banke CTO
Technical implementations unblocked
I also help AI startups clear technical implementation roadblocks to improve the product and secure funding.
BeroAI Real-time voice agent
$1M Funding secured
10% → 95%+
RAG accuracy 5% → 95%+
Tool call reliability 10x
Latency reduction "Sheila helped us redesign our entire AI architecture. She exceeded all our expectations and I can't recommend her highly enough."
Ken Rees Founder & CEO
AI news service
2 Weeks to prototype
€1M Funding secured
Blocked → Clear implementation path
Core feature Standstill → Validated
Product status "Sheila put together the technical approach for a key product feature very quickly and it was exactly what we needed."
Aleksi Kaistinen Founder
I'm Sheila Teo.
Orso is my independent AI engineering practice.
I started Orso because I kept seeing enterprise teams invest in AI tools without real business ROI. These helped people move faster, but isolated productivity gains don't translate meaningfully into business impact. The workflows that actually drive the business must change. That gap is where I deliver: Determining one high-value workflow, redesigned into a live AI agent system in 8 weeks, with business impact you can measure immediately.
Columbia Engineering, Ex‑FAANG. 6+ years shipping production AI across enterprise, government & startups. Winner of 2× LLM competitions. 300K readers from my technical AI writing.
Across every engagement, I've delivered:
6+figures
ROI per enterprise7+figures
raised per startupYou work directly with me
From system design to code to deployment — I build the AI system for you, or embed with your engineers and build it together in your codebase.
Same specialist, start to finish. No junior handoffs, no coordination tax.
For larger work, I bring in my network of elite AI engineers and stay personally accountable for delivery end-to-end.
Google 
Apple 
Meta 
NVIDIA 
Stripe 
Amazon 
TikTok Google Apple Meta NVIDIA Stripe Amazon TikTok Google Apple Meta NVIDIA Google Apple Meta NVIDIA Stripe Amazon TikTok Stripe Amazon TikTok You own what I build
Your team understands and operates the AI system without me.
What companies notice
You stay ahead of the field.
AI moves fast, and your team's plate is already full. Tracking the frontier is what I'm here for.
It's where I live: competing, writing, speaking, and building alongside engineers at the top of this field.
Companies bring me in when they need more than a generic AI engineer. They also want:
1
Someone who flags what's worth your attention — before it's on your radar.
"Sheila is the person who helps us understand what in AI can actually create business value for us. She consistently brings us new developments that can be immediately applied to a real challenge we have."
Ted BrownDirector | Ntiva, Inc.
2
Someone who leaves your internal team stronger.
Because great AI talent is hard to find and expensive to hire. When I work with your team, you don't just get a finished AI system. I care about transferring what I know onto your engineers, and about being someone you'll be glad you worked with.
"Sheila makes the people around her better at AI. She's generous with what she knows, explains things clearly, and leaves you with judgment you keep using after the project is over."
Ken ReesCEO
FloatMe
"I learned so much from working with Sheila that still helps me to this day!"
Troy CosentinoSenior AI FDE | fal.ai
FAQ
Process
The diagnostic call is a working session where I review your operational pain points with you. You leave with an initial diagnostic of where AI could measurably reduce operational overhead, accelerate execution, or replace manual work.
My guarantee: You leave with at least 1 actionable insight. No obligation to work together after.
I evaluate each candidate on 4 axes: ROI, feasibility, risk, and production complexity. A strong fit has repeated work, clear business impact, available data, a workflow owner, and a path to daily use in your operations.
Build
Every agent is built to order, fitted to your workflows, your systems, and your business requirements. It fully integrates with the enterprise stack you already run.
Most engagements move from discovery to a production agent system in 6 – 12 weeks, depending on workflow complexity and the systems involved.
My goal for you: Avoid a 12-month transformation program. I start with a bounded workflow that delivers ROI quickly, then expand as needed.
Your team provides context on the workflow and the systems involved so what I build matches how work actually happens. This takes roughly < 20 hrs total across all your employees, concentrated in the first 2 weeks of discovery.
Afterwards, I handle all AI development and deployment while keeping your teams in the loop. That is, unless your team wants to be part of the development too!
Trust
Data privacy and security are designed into your agent systems upfront — both what data your agents can access, and what data is retained by model providers.
If your enterprise isn't already on a Zero Data Retention agreement with your chosen provider, I'll walk you through the process.
Your data stays yours only. It won't be stored or used by me, or by the model providers.
I closely monitor the agent system after deployment. Performance, failures, exceptions, and business impact are quantitatively tracked and used to improve the system over time.
You get a live KPI dashboard tracking agent performance, cost savings, and time recovered. I stay with you until the system is optimized.
I don't hand you an agent and walk away.
Engagement
Engagements are scoped based on workflow complexity and integration depth, with agreed success metrics before build begins. I share full pricing once I understand scope. Most enterprises that work with me recover cost within 120 days of production, and spend far less than it takes to hire an in-house AI engineering team.
Get in touch.
Explore how AI agents could transform your company's workflows.
My guarantee: You leave with at least 1 actionable insight. No obligation to work together after.
Best 30 minutes we have ever spent. Sheila understood the problem quickly and gave us a ton out of our time.
Sheila unraveled why our previous AI approach wasn't working and helped us see what would actually be worth building.
Sheila's engineering expertise is remarkable. We struggled for weeks with challenges that she resolved in hours.