BeFaster
Less time is spent collecting facts manually across functions and systems.
BeSmart · AI Transformation Studio
AI agents automate production and operational processes.
They connect context across systems, prepare decisions and guide execution. People set the boundaries, approve critical steps and remain accountable for outcomes.
How a managed action emerges
Describe a troubled process. BeSmart will design the operating loop.
Start with the problem: where the business loses time, money or control. BeSmart connects data, roles and processes so decisions arrive while there is still time to act.
We do not replace ERP, EAM, MES or SCADA. We add AI, workflow and execution control on top of the existing environment.
Explore the pilot path →Unified operating system
Signals, decisions and execution — in one loop.
Select a step to see how an equipment signal becomes a verifiable maintenance request with an owner, deadline and approved substitute parts.
Example: critical pump failure
06 steps
Incoming signal
SCADA: rising vibration on pump P-204
The event is recorded, but the cause, severity and required action are still unknown.
InputEvent code + timestamp
OutputDeviation record ready for analysis
More reliable
Sources, assumptions and review points are visible before a decision.
More controllable
The deviation, action, owner, deadline and execution outcome are visible.
Product architecture
The BeSmart operating stack.
One end-to-end loop: from a signal in enterprise systems to a prepared action and an accountable human decision.
Signal
An event, document, deviation, request or management task.
Data
ERP, EAM, MES, PLM, SCADA, documents and enterprise databases.
Context
Facts, roles, policies, history and constraints for the situation.
Workflow
Review, approval, action, escalation and deadline control.
MCP Server
A single connection point for approved tools and services.
AI agents
Assemble context, prepare action options and guide execution.
Control
Approval of critical steps, with a visible decision and outcome history.
Foundation
Built on top of the existing enterprise IT landscape
Security
Deployment inside the enterprise perimeter
On-premise · Enterprise-grade data security
One platform · multiple operating loops
Not isolated AI pilots. One system for change.
Data, process, AI and control are designed together. Open each layer to see its role in the overall system.
05
Process AI agents
They operate as participants in a specific process, not as a generic chat — with approved sources, tools and human handoff points.
- Context collection and validation
- Explainable action preparation
- Execution guidance
- Process coordinator plus data, policy, deviation and action agents
04
Control layer
Separates AI preparation from accountable decisions. Authority, constraints and approval points are defined for every use case.
- Roles and accountability
- Approval of critical actions
- Decision and execution history
- Levels: observe → recommend → prepare → act with approval
03
Enterprise workflow
Connects actions across production, maintenance, procurement, finance, safety and management.
- Action owner and deadline
- Handoffs between roles
- Escalations and control points
- Measurable process outcome
02
Operational context
Brings facts from systems and documents into a single situation that is ready for a decision, not merely display.
- Data and documents
- Policies and constraints
- History of similar situations
- REST API, webhooks, SQL, CSV/XLSX and MCP Server; industrial protocols through an approved gateway
01
AI Transformation Studio
One BeSmart team owns the journey from process diagnosis and impact hypothesis to a working product and operational handover.
- Process diagnosis
- Product design
- Development and integration
- Operational launch
From sourcing and supply to equipment reliability
One principle: the decision must arrive in time to affect the outcome.
We start with one process, measure impact against baseline KPIs, and only then expand the operating loop to adjacent functions.
From hypothesis to a working operating loop
12 weeks to prove one business hypothesis.
Select a process
Define the problem, the owner and the point where time or value is lost.
Capture the baseline
Define current KPIs, constraints and criteria for a successful pilot.
Assemble context
Connect the available data, documents, roles and process rules.
Build the product
Design the workflow, agent responsibilities and human control points.
Test in operations
Test real scenarios, capture errors and adjust operating boundaries.
Measure impact
Compare results with the baseline and decide whether to scale.
Control does not disappear. It becomes explicit.
Agents do the work. People make the decision.
AI agent
Prepares and guides the action.
- Collects facts from approved sources
- Checks rules and constraints
- Explains risk and uncertainty
- Tracks execution and deviations
Accountable role
Sets boundaries and owns the outcome.
- Approves criteria and authority
- Confirms critical actions
- Resolves ambiguous cases
- Decides whether to scale
Application areas
Start where the cost of manual coordination is already visible.
01 / Materials & procurement
Specifications, inventory, substitutes and purchasing
Problem
Finding substitutes and approving disputed items spans PLM, ERP, policies and subject-matter experts.
How it works
The agent assembles specifications, inventory and constraints, explains matches and routes exceptions for review.
Pilot impact hypothesis
Reduce substitute selection and approval from several days to a few hours.
What we measure
Median selection time, automatically matched items and rework rate.
BeSmart · AI Transformation Studio