Thesis
From operational chaos to predictability.
The thesis Praxis is built on — and how we work with every client.
In industrial and energy companies in Iberia, day-to-day operations are marked by an invisible but expensive fragmentation. Management systems exist; the connective tissue between them is missing, and so is the method to weave it.
The four symptoms of operational chaos
Excel as a system
Excel becomes the unofficial main system. Data is duplicated and manually manipulated. Multiple versions of truth coexist.
Data in silos
Vital information isolated in emails, CRMs, ERPs and network folders. Seeing the business as a whole, in real time, is impossible.
Irreplaceable heroes
Operational success depends on the heads of a few specialists. Tacit knowledge nowhere documented.
Repetitive tasks
Skilled teams typing invoices and triaging tickets. Systematic underuse of talent.
The same operation, two outcomes.
On the left: how most industrial back-offices look today. On the right: what Praxis builds. Same data, same systems, different method.
Before
Operational chaos
Errors
↑
Time
↑
Risk
↑
After
Praxis operation
STP
↑
Cycle time
↓
Hours freed
↑
What defines a Lighthouse Project
More than tools.
A Lighthouse Project is an intervention that shifts a culture from "firefighting" to data-driven operations.
Structured in three layers:
01
Data
Consolidating ERP, sensor, CRM and billing flows into a single source of truth.
02
Intelligence and semantic model
The LLM doesn't read raw data. It reads a semantic model — logical tables of customers, invoices, operations. It answers with those definitions and business rules, instead of guessing what each column means.
03
Interaction and channels
Chat (Teams, Slack, portals), web interfaces and integrations with the tools people already use.
Traditional vs. AI-assisted
The common thread is design for exception: AI processes the volume, and people step in where judgment adds real value.
| Domain | Traditional flow | Praxis flow | Impact |
|---|---|---|---|
| Industry · Invoices | Manual PDF typing into ERP. Posting errors, delays, lost early-payment discounts. | Intelligent JSON extraction with OCR + LLM. Automated 3-way match (invoice, PO, receipt). | Manual typing only for exceptions. Lower fine risk. Better cashflow. |
| Energy · EV Operations | Manual navigation across silos (billing, CRM, EV platforms). Diagnosing offline stations or billing errors takes time. | Operations copilot with natural-language queries. Identification of charge session anomalies. | Answers without jumping between systems. Anomalies caught earlier, protecting uptime. |
| HR · Helpdesk | Teams overloaded with repetitive FAQs. Sensitive tickets lost in vacation-balance noise. | Transactional AI agent solves queries and executes actions (HCM, ITSM). Smart escalation on sensitive topics. | HR time freed from repetitive questions. Human focus dedicated to talent management. |
The three KPIs that measure all of this.
For C-level, AI must stop being hype and move EBITDA, margin and risk.
STP
% Automation
Volume of processes completed without human touch. Straight-through processing as the primary metric.
Time
Cycle Time
Acceleration between data entry and accounting/resolution. Cashflow and SLA depend on this.
Capacity
Hours Freed
Skilled hours recovered for strategic work. Reduces operational cost per transaction.
From fragmentation to predictability.
We treat automation as a strategic capability of the company, not as an isolated IT project.
“Strategy without execution is PowerPoint. Execution without strategy is fireworks.”