Do Favoriot need to develop an AI Agent feature?
Short answer? No, Favoriot does not need full AI Agent automation right now.
And yes, what you have today is more than enough for the market you are serving.
Let me explain this the way I usually reason with myself.
I asked myself this quietly
“Do customers really want systems that act on their own…
or do they want systems they can trust?”
When I sit with city operators, facility managers, engineers, or even researchers, one thing keeps coming up.
They are not asking for autonomy.
They are asking for clarity.
They want fewer surprises.
They want earlier signals.
They want confidence before taking action.
That matters.
What Favoriot already does well
Right now, Favoriot Intelligence does something very important and very rare.
It learns patterns from real operational data
It surfaces what looks unusual
It feeds those insights into a Rule Engine
And then… it stops
That stopping point is not a weakness.
It is a design choice.
The system says,
“Here is what changed.
Here is why it matters.
You decide what to do next.”
That is precisely where trust is built.
Rule Engine + ML is not a compromise
Some people frame this as:
“Rule Engine now, AI Agents later.”
I don’t see it that way.
I see it as:
ML decides what deserves attention
Rules decide what action is allowed
This separation is powerful.
Why?
Because rules are:
- Auditable
- Explainable
- Governable
- Aligned with SOPs and regulations
And ML is:
- Adaptive
- Pattern-driven
- Good at spotting drift and anomalies
Together, they form a human-in-the-loop intelligence system, not a black box.
That is exactly what enterprises and public sector teams are comfortable with today.
Do customers actually want AI Agents?
Here’s the uncomfortable truth.
Most organisations say they want AI to “automate everything”.
But when you ask one more question…
“Are you okay if the system shuts down equipment on its own?”
“Are you okay if it triggers evacuation automatically?”
“Are you okay if it changes operating parameters without approval?”
The room goes quiet.
What they really want is:
- Earlier warnings
- Better recommendations
- Fewer false alarms
- Less manual rule tuning
Favoriot Intelligence already delivers that.
Where AI Agents actually make sense later
I’m not against AI Agents. Not at all.
But their place is conditional, not universal.
AI Agents make sense when:
- Policies are mature
- Actions are reversible
- Risk is low
- Trust has been earned over time
For example:
- Automated report generation
- Recommendation ranking
- Suggesting rule adjustments
- Proposing actions for approval
Notice the word: suggesting, not executing.
That is a natural evolution path.
Not a starting point.
Strategically, Favoriot is in the right place.
By keeping:
- ML for learning and insight
- Rules for control and action
Favoriot positions itself as:
- Reliable
- Safe
- Deployable today
- Acceptable to conservative sectors
Smart cities.
Utilities.
Campuses.
Critical infrastructure.
These sectors do not reward “full autonomy” first.
They reward predictability and confidence.
My honest conclusion
If I had to answer this as simply as possible:
Favoriot does not need AI Agents to be valuable.
Favoriot Intelligence with ML-driven rules is already the right solution for today.
AI Agents can come later, carefully, selectively, and with guardrails.
Right now, Favoriot is doing something more important than automation.
It is helping people think earlier, not react later.
And that, in my book, is real intelligence.
Dr. Mazlan Abbas 