It's not three services. It's one flow: capture, integrate, analyze, decide, and act.
Every stage has an owner, evidence, and — where it applies — a real case backing it up.
From sensor to decision, with no black box.
Senses the physical world
Sensors, devices, and field systems.
Go deeper → DataIntegrates and cleans it
Unifies scattered sources into trustworthy data.
Go deeper → AIInterprets and decides
Models that can explain how they got there.
Go deeper → ActionActs
Automation, alerts, or decisions executed.
Go deeper →Pick a stage and see exactly what BIT does there.
Every node shows whether it's already proven in real projects or still in development — no dressing up the actual state of the portfolio.
Data
Capture Proven
Forms, sensors, transactional systems, and public sources.
Integration Proven
ETL and APIs to unify heterogeneous sources.
Quality Proven
Validation and data governance, consistent with BIT’s audit standard.
Processing Proven
Spark and PySpark at scale, on distributed architectures.
Analytics Proven
Predictive modeling, fraud analysis, sentiment analysis.
Visualization Proven
Dashboards and reporting for business decisions.
AI
ML / Deep Learning Proven
Computer vision, NLP, and predictive models.
Generative AI Proven
Generative models applied to concrete business cases.
Agents & automation Proven
Process automation backed by AI models.
Prediction Proven
Predictive models for oversight and decision-making.
Assisted decisions Proven
Governed under the ISO/IEC 42001 audit standard at every stage.
IoT
Sensing & acquisition Proven
Electronic instrumentation, already part of BIT’s portfolio.
Connectivity Proven
VoIP, networking, and connectivity solutions.
Telemetry In development
Backed by the founder’s historical experience in industrial telemetry.
Data platforms In development
The convergence point with the Data lane.
Actuation In development
Automation or alerts on the physical world, driven by the decision made.
Most vendors sell AI. We deliver the full pipeline — and can show you every step.
No black box
Every AI decision traces back to the data that produced it.
No loose promises
Every stage is backed by a real case, or honestly marked as in development.
One team
Whoever builds the system is who audits it — not two separate vendors.
Here's this flow working in real projects.
Hadoop/HDFS + PySpark Cluster
A data volume that exceeded what traditional tools could process efficiently.
Distributed processing architecture validated; exact production impact pending confirmation with the specific client project that put it into production.
Large-Scale Accounting Data ETL for a Logistics Company
A logistics company had years of accounting and financial information scattered across multiple sources, with no unified process to consolidate or make use of it.
Significant time and money savings for the company, by eliminating manual, scattered processing of accounting information.