Tommi's slides for talk about Small AI in RPA in the HelTech online event on Oct 5 2020.

1. Small AI is
the next big
thing in RPA
@tonni
@aitodotai
#brains4bots

3. RPA overview
Execution of a repeatable task performed by a software robot,
often involving manipulating an UI like a human would do.
Read new
employee record
from HR system
Combine with
job contract
data
Enter data in
to payroll
system

4. + Availability and speed
+ Avoid costly IT projects
+ Great for narrow tasks and
working alongside human
- As smart as the rules
given to it
💓 💔

5. When if-else becomes impossible
Complexity
Totalcost
Rule-based

6. RPA becomes IA
Complexity
Totalcost
Rule-based
Machine
learning

7. Big ML vs Small ML
Complexity
Totalcost
“85% of AI
projects
fail”
High efficiency

8. Starting and staying small makes sense
Don’t settle with
months of data
science backlog
wait time.
Build with
existing team
and stay agile
Avoid high
maintenance
costs of “big
ML” infra
Plan Build Maintain

9. New capability of an RPA team
“Aito has provided Posti a fast
and easy tool to implement
machine learning to business
processes, adding new
opportunities to our Intelligent
Automation toolkit.”

11. Some APIs to check out
Amazon AWS
Comprehend, Textract, Transcribe, Forecast
Google Cloud Platform
Document AI API, Form Parser
Azure ML Studio
Aito (!;)

12. Aito changes the ML workflow
Business
needs
Data prep
Feature
engineering
Model
training
Model
evaluation
Model
tuning
Productionise
model
Deploy
model
Integrate
predictions
Monitor
predictions
Aito predictive query
{
"from": "invoice_data",
"where": {
"Inv_Amt": 83.24,
"Item_Description": "File Management",
"Vendor_Code": "VENDOR-1676"
},
"predict": "GL_Code",
"limit": 3
}

13. Start seeing use cases everywhere
Fix a datapoint
that often is
missing, and
prevents the
completion
Bot makes the
decision based on
human learned
patterns
Save the sanity
of a developer by
replacing complex
rules
Avoid and
identify
duplicates in CRM
database
Identify
anomalies in hour
reporting and
customer
invoicing
Categorise and
prioritise
customer support
tickets based on
their impact to
NPS