Bring up weak signals sooner, before they turn into visible greenhouse-wide issues.
Decodoc — understand documents, even across languages.
An EIREEN Tech app that helps analyze, translate, and summarize documents so people can quickly understand what it is, what is being asked, deadlines, risks, and next steps.
Available on the App Store and Google Play.
Spot greenhouse problems earlier.
EIREEN brings climate data, sensors and operational logs into one clear view, then turns weak signals into actions your team can actually use.
Less guesswork. Less time lost between spreadsheets, dashboards and intuition. More visibility for field teams and management.
Combine zones, climate, history and field observations into one operational picture.
Turn complexity into understandable next steps that can be shared across the team.
What does EIREEN actually help you do?
EIREEN helps teams move faster from signals to decisions without piling on another dashboard or losing operational context.
See earlier
Surface weak patterns before they turn into more expensive crop, quality or planning issues.
Understand faster
Connect climate, irrigation, field notes and history into a view people can actually interpret and act on.
Act more clearly
Give the team an understandable next step with priority, context and a clearer handoff.
A simple chain: collect, unify, analyze, act.
The goal is not another analytics layer for its own sake. The goal is to structure useful information so decisions get faster and more confident.
Collect
Sensors, climate systems, images and field logs feed a shared operational base.
Centralize
Data is organized by greenhouse, zone, crop batch or time period in one consistent structure.
AI analysis
Anomalies, weak signals, deviations from baseline and history comparisons become easier to interpret.
Recommendations
The platform highlights priorities, suggests actions and keeps a traceable operational history.
Visual blocks that explain the product instead of hiding it behind abstract dashboards.
Each visual answers a practical question: where to look, why it matters and what to do next.
Greenhouse / zone view
A readable map of areas with status, trends and attention points so teams can localize issues quickly.
Early alerting
Abnormal patterns explained and ranked in a more useful way than a raw alert feed.
Action recommendation
A suggested next step with urgency, context, explanation and a clear operational owner.
Trends and history
Time-based context that helps teams understand what is really changing and validate decisions.
A clarity layer between raw signals and operational decisions.
EIREEN is meant to reduce information overload and improve alignment across field teams, agronomy, management and technical partners.
React earlier
Catch deviations sooner and reduce the cost of late-stage corrections.
Coordinate teams better
Give operations, agronomy and multi-site management a shared operational reading.
Reduce information overload
Move from scattered signals to a ranked list of what actually deserves attention.
Decide with more confidence
Support decisions with clearer context, more structure and a better sense of priority.
Designed for operators, agronomists, multi-site teams and technical partners.
The platform is structured to be useful both for daily greenhouse operations and for the people designing, deploying or supervising the systems around them.
Greenhouse operators
For clearer production oversight and better visibility into zones and deviations.
Agronomists
For combining field expertise, historical data and weaker signals without losing context.
Multi-site groups
For comparing sites in a shared framework and coordinating interventions faster.
Tech & automation partners
For connecting existing systems to a clearer decision support layer.
Pilot sites
For validating real use cases, documenting operational value and co-building the product.
An architecture built to consolidate heterogeneous data sources and turn them into operational decisions.
The value is not just in gathering data. It is in connecting sensors, systems and historical records to an analysis and recommendation engine.
Connected inputs
Climate data, sensors, automation systems, operational history, field observations and, over time, image and camera streams.
Platform core
Data consolidation and normalization across sources.
Anomaly detection and interpretation by zone, pattern and time window.
A recommendation engine that surfaces the next useful operational action.
A structure designed for a working MVP first, then secure scaling.
A founding team spanning structuring, innovation, architecture and go-to-market.
The roles are intentionally complementary: project leadership, innovation methodology, technical architecture, commercialization and partnerships.
Konstantin Lekomtsev
Strategy, partnerships, France pilot and ecosystem development.
Alexei Leshchev
Innovation methodology, R&D logic and grant ecosystem support.
Denis Lekomtsev
Platform architecture, data integrations, security and scalability.
Georgii Ilin
Positioning, marketing, lead generation and commercialization support.
Want to structure your data, detect problems earlier or explore EIREEN as a pilot site?
The next step can stay simple: an exploratory call, an integration discussion, a pilot conversation or a focused demo.