Industrial data analytics for plants that can't afford downtime.
We turn sensor, machine, and lab data into early warnings, maintenance decisions, and traceable research results. Built on our own infrastructure, running inside your operation, with your data always in your hands.
Problems we solve
Downtime you could have seen coming.
The machine warns weeks ahead through changes in vibration or temperature. No one is reading that signal.
Data that exists but isn't used.
The PLC, the SCADA system, and the spreadsheets hold years of history that never get cross-referenced.
Tools that aren't yours.
Third-party cloud platforms, billed per sensor, with your data living outside your company.
Service lines
That's why we built three service lines, one per problem.
Monitoring & predictive maintenance
Read the signal before the failure
We read the signal from your equipment and detect the failure pattern before the downtime.
- Diagnosis of critical assets and available signals
- Anomaly detection models by frequency (vibration, current, temperature)
- Alerts wired into your maintenance flow (email, WhatsApp, CMMS)
Data engineering & platforms
A reliable, traceable data foundation
We build the foundation so your operational data is reliable and traceable.
- Integration of PLC, SCADA, ERP, and spreadsheets
- Governed data platform, local, on-premise, or cloud
- Operational dashboards and downloadable reports
Scientific & technical data analysis
Exact computation, full traceability
We process research and lab data with exact computation and complete traceability.
- Ingestion of scientific formats (HDF5, NetCDF, NumPy, Parquet)
- Signal analysis, time series, PCA and SVD
- Auditable log of every data transformation
Industries
These lines are already applied across the following sectors.
Manufacturing & production
Predictive maintenance, process quality, costing with Korest.
Agribusiness
Field sensors, irrigation, cold chain.
Energy, fleets & buildings
Monitoring of distributed assets.
Research & health
Labs, universities, and applied science projects.
Don't see your sector? We also build auditable semantic search over internal documents, pattern detection, and custom systems.
We build the tools we use and the products we run
We can offer this at this price and speed because we don't depend on a third party: we build our own infrastructure.
We don't depend on a third party's platform to analyze your data. Our analytical engine, linalDB, unifies business data, sensor signals, and mathematical computation in a single system that can run inside your plant.
Infrastructure
Our own analytical engine: hybrid tables mix business columns with vectors and matrices, native FFT/PSD/BANDPASS signal functions, and a single embeddable binary that runs inside your plant. Community-licensed and inspectable, so your system keeps working even if we're not.
Learn more →The framework we use internally for ingesting, processing, validating, and exposing data. Open-source, built on reproducible pipelines instead of one-off scripts. Runs the same locally, on-premise, or in the cloud, and you can adopt one piece of it at a time.
Learn more →We apply the same approach to other businesses: pick a niche, understand it deeply, build it the exact tool it needs.
Other products we run
Case studies
This is what it looks like in practice.
While we document our first fully industrial case, this is how we think: systems that replace spreadsheet chaos with real control.
KeeperCase
- Problem
- The company struggled with scattered information across multiple spreadsheets, making it difficult to maintain accurate pricing, track material costs, and generate professional quotations quickly. Each quote required manual calculations and cross-referencing multiple files, leading to errors and inefficiencies.
- What we built
- We built a custom ERP-lite system that centralizes product catalogs, material costs, and pricing logic. The platform automates quotation generation, tracks inventory, and maintains a complete history of customer interactions. The interface was designed for craftsmen, not accountants, intuitive and focused on their daily workflow.
- Result
- The system is now the central hub for all quotations and customer management. Quote generation time reduced from 30+ minutes to under 5 minutes. The team can now track profitability per project and maintain consistent pricing across all customers.
Our way
This is how we work to get to that result.
- Small teams, big impact
- Craft over hype
- Partnership > projects
Discover
Listen, map constraints, align goals
Prototype
Fold ideas into interactive flows
Build
Front, back, design, deploy
Evolve
Metrics, iterations, scale
At the end of the project, the system and the data are yours.
Team & track record
Behind that process is a team with a verifiable track record.
A small group of engineers, designers, and builders, focused on creating data systems that last.
Nicolás Balaguera
FOUNDER · DATA ENGINEERING
More than 12 years building data platforms. Fraud analytics (Nubank), GCP data platforms (Kin + Carta), and data governance for fintech (Cashea). Creator of linalDB.
David Barbosa
FULL-STACK DEVELOPER
Turns data pipelines and analytics engines into reliable interfaces and production-ready software.
Jennifer Concha
DESIGN & MARKETING
Translates technical findings into dashboards and reports that a plant manager can act on.
Bogotá, CO. Building globally.
Tell us which machine, dataset, or question is keeping you up at night.
No layers. No noise. A small team that listens, thinks, and delivers.