Our grow team already uses a SCADA system for climate control. Can you build software that connects to it rather than replacing it?

Yes. Most vertical farm builds we scope involve integrating with existing SCADA, PLC, or BMS infrastructure rather than replacing it. We connect to your existing control layer via OPC-UA, MQTT, or Modbus protocols, pull real-time telemetry into a unified data platform, and build the analytics, alerting, and planning tools on top. Your grow team keeps the control interface they know; you gain the data layer they need.

Can you build a yield forecasting system that accounts for our specific crops and grow-room variables?

Yes. Yield forecasting for vertical farms is crop-specific and environment-specific, which is why generic agriculture software tools produce forecasts with wide error bands. We build forecasting models trained on your historical grow data, factoring in your cultivars, lighting schedules, nutrient programs, and room-level climate variables. The output is a forecast your sales team can commit to, with confidence intervals that narrow as the harvest date approaches.

How long does a vertical farming software project take and what does it cost?

A first module, such as a climate monitoring and alerting platform or a grow-cycle tracking system, launches as a validated v1 in about 12 to 16 weeks. You grow it from there. A full operations platform covering climate control integration, grow-cycle management, yield forecasting, energy dashboards, and harvest planning runs 18 to 28 weeks of build. Cost depends on the number of sensor integrations, grow rooms, and forecasting complexity, and is fixed before development starts.

Can you integrate with our existing sensor hardware and cloud platforms like AWS IoT or Azure IoT Hub?

Yes. We build integrations with AWS IoT Core, Azure IoT Hub, and direct MQTT broker connections from sensor hardware including Modbus-based environmental sensors, CO2 monitors, and smart lighting controllers. If your hardware already sends data to a cloud endpoint, we connect to that stream. If it does not, we scope the IoT gateway layer as part of the project.

We are evaluating off-the-shelf vertical farming software versus building custom. How do we know which is right?

Off-the-shelf vertical farming platforms work well when your crop mix, facility layout, and operating model match the assumptions the platform was built around. Custom development becomes the right choice in four cases. Your facility has non-standard grow-room configurations. You sell into channels that require specific traceability reporting. Your energy tariff structure needs optimization logic the platform does not support. Or the platform's per-seat pricing becomes a constraint as you add grow rooms. We scope what needs to be custom versus what can use an off-the-shelf component during discovery.

Do you build mobile apps for grow team field use inside the facility?

Yes. Grow team workflows (batch record entry, environmental spot checks, pest and disease logging, transplant confirmations) are best captured on a mobile device at the point of work rather than typed up later at a desktop. We build iOS and Android apps, or React Native cross-platform apps, that work offline inside the facility and sync to the central system when connectivity is restored. Offline-first design is a requirement for in-facility mobile tools, not an optional extra.

Our best grower carries years of operational knowledge in their head. Can software protect us when they leave?

This is the single largest institutional risk for growing operations. When crop recipes, environmental adjustment strategies, and troubleshooting intuition live exclusively in one person's head, you're one resignation away from losing years of operational learning. We build grow-cycle management that captures the recipe as data: every batch records the cultivar, the lighting schedule, the nutrient program, and the environmental history. The knowledge becomes the system's, not the resignation letter's.

AI in vertical farming software development

A facility might have $2 million worth of environmental control equipment generating thousands of data points per hour, but the production manager is manually entering harvest weights into a Google Sheet that doesn't talk to the financial model. What is your true cost per pound? Most operators know their top-line revenue and rough cost structure but can't confidently say which crops are actually profitable. Every photon in a fully indoor vertical farm has to come from somewhere. The crop must generate enough value to pay for the electricity used to grow it.

Climate control automation that catches excursions in minutes, not hours, with alerting built around your crop's tolerance thresholds
Grow-cycle management software that tracks every batch from seed to harvest in one system, replacing disconnected grow logs
Energy optimization dashboards that show cost-per-kilogram by room and shift, so you cut the right spend without touching yield
Harvest and sales planning tools that give your buyers accurate volume and quality forecasts 14+ days out

The problem

Sound familiar?

Climate excursions going unnoticed for hours because sensor data lives in one tool, alerts in another, and your grow team checks both manually?
Energy bills that account for 30-40% of operating costs but no dashboard that shows which grow room, which lighting schedule, or which HVAC event drove the spike?
Yield forecasts built in spreadsheets three days before harvest, leaving sales teams with no reliable forward visibility on volume or quality?

Short answer

RaftLabs builds AI in farming software for vertical farm, CEA, hydroponic, and urban farm operators: AI-trained yield forecasting models, climate control automation, grow-cycle management, energy dashboards, and harvest planning. A first module launches as a validated v1 in about 12 to 16 weeks. We scope every project before pricing: fixed cost, agreed before work starts. The full operations platform grows from there.

Trusted by

01 Diagnosis

Where vertical farm operations actually leak

01
Problem
Climate excursions go unnoticed until they show up in yield
Solution
Most vertical farms collect environmental data from dozens of sensors across temperature, humidity, CO2, VPD, and lighting. The data goes into a SCADA or data historian, and someone reviews it during shift changes. By the time a temperature excursion in grow room 4 appears in the morning report, the crop has been outside its optimal range for six hours. At the margins that vertical farming operates on, six hours of suboptimal VPD during a critical growth stage shows up directly in harvest weight and quality.The underlying problem is not the sensors. Sensor data, alerting rules, and grow team response workflows live in separate systems with no shared logic. Custom climate monitoring software connects sensor telemetry to crop-specific alert thresholds. It routes notifications to the right person on shift via SMS and in-app alerts, and logs every excursion against the affected batch, so post-harvest analysis has the data it needs. The outcome is minutes, not hours.
02
Problem
You can't optimize what you can't measure
Solution
Electricity for LED lighting and HVAC climate control accounts for 30 to 40% of total operating costs in a typical vertical farm, making it the single largest variable cost item. Labor and energy together run about 60% of the cost of running an indoor farm. Most operators know their monthly bill. Few can tell you the cost-per-kilogram by grow room, by crop, or by lighting schedule, because that data means joining energy sub-metering with batch-level production records, and spreadsheets never do that consistently across many rooms.Without that visibility, energy reduction efforts are guesswork. An energy optimization dashboard built on your sub-metering data and grow records gives you that answer at the room and shift level, so every efficiency decision is grounded in actual cost-per-output data. The outcome is the crop paying for its own photons.
03
Problem
Generic ERPs don't understand growing
Solution
Generic manufacturing and food processing ERPs fail in CEA because they don't understand growing cycles, environmental interdependencies, or the biological variability inherent in crop production. Vertical farm sales teams need accurate forward yield forecasts to commit to retail and foodservice buyers 10 to 21 days ahead of harvest. Most operations produce those forecasts from grow logs and historical averages, assembled in spreadsheets a few days before harvest.Custom yield forecasting software built on your actual grow data, incorporating real-time environmental readings and cultivar-specific growth models, produces forecasts 14 or more days ahead of harvest with error bands your sales team can plan around. The outcome is commitments you can keep.
04
Problem
The grower's knowledge walks out the door
Solution
When your best grower's crop recipes, environmental adjustment strategies, and troubleshooting intuition live exclusively in their head, you're one resignation away from losing years of operational learning. Regulatory traceability requirements for food safety require a documented chain from seed lot to harvest batch with environmental records attached. Most vertical farms meet that requirement with a patchwork of paper grow logs, spreadsheet batch records, and SCADA exports assembled manually when an audit arrives.A unified grow-cycle management system creates a digital record for every batch from seeding through transplant to harvest, attaches the environmental data automatically, and produces the traceability report in minutes rather than hours. The outcome is institutional knowledge that survives the resignation.

02 What we ship

Vertical farming software we build

Climate control and monitoring systems
We connect to your existing sensor hardware and SCADA or PLC infrastructure via OPC-UA, MQTT, and Modbus protocols, pulling real-time telemetry from temperature, humidity, CO2, VPD, and lighting sensors into a unified monitoring platform. Crop-specific alert thresholds trigger notifications via SMS, email, and in-app alerts routed to the right grow team member on shift. Excursion logging attaches every out-of-range event to the affected batch record automatically, so post-harvest analysis has the data without manual cross-referencing.
Built for vertical farms and CEA facilities that collect environmental data but cannot act on it fast enough because the data, alerts, and batch records live in separate systems.
Grow-cycle management software
A single digital record follows every batch from seed lot receipt through germination, propagation, transplant, grow, and harvest. Grow team inputs, nutrient program adherence, substrate checks, and pest or disease observations go into the same system rather than across clipboards, spreadsheets, and shift handover notes. Batch records carry the full traceability chain: seed lot number, transplant date, grow room and rack position, environmental history, input quantities, and harvest outcome.
Built for vertical farms adding SKUs, grow rooms, or market channels where manual record-keeping is becoming the operational bottleneck.
Yield analytics and forecasting
Yield forecasting models trained on your historical batch data factor in cultivar, grow room, lighting schedule, nutrient program, and current-cycle environmental readings to produce harvest weight and quality predictions 14 or more days ahead of cut date. Forecast confidence intervals narrow as the harvest date approaches and more grow-cycle data is available. Performance analytics break down yield-per-rack, yield-per-watt, and cost-per-kilogram by grow room, crop, and time period.
Built for vertical farm operations teams that need to give sales buyers reliable forward commitments and for operators building the data foundation to optimize across multiple facilities.
Energy optimization dashboards
Sub-metering data from lighting circuits, HVAC systems, irrigation pumps, and nutrient dosing equipment joins batch production records to produce cost-per-kilogram at the room, crop, and shift level. Lighting schedule optimization analysis shows which photoperiod changes reduce energy draw without measurable yield impact, based on your own historical data rather than generic benchmarks. Energy spend is reported by time-of-use tariff period so facilities on demand-response contracts can shift flexible loads.
Built for vertical farm operators where energy is the largest cost line and where current reporting only shows total spend, not the room-level and decision-level breakdown needed to cut it.
Harvest and sales planning tools
Harvest calendars aggregate projected cut dates, estimated volumes, and grade distributions across all active batches, giving your sales and operations teams a shared forward view of available product. Sales order allocation against forecast volume flags over-commitments before harvest, not after. Customer-facing harvest availability reports in PDF or via API feed buyer procurement systems directly. Post-harvest waste tracking ties actual versus forecast variance back to the grow-cycle and environmental records.
Built for vertical farms selling into retail, foodservice, or wholesale channels where reliable forward commitments determine whether you keep or lose accounts.
IoT integration and data infrastructure
We design and build the data infrastructure layer that connects sensor hardware, SCADA systems, ERP platforms, and cloud services into a coherent operational data store. Integrations cover AWS IoT Core, Azure IoT Hub, MQTT brokers, Modbus and OPC-UA industrial protocols, and REST APIs from existing farm management tools. Data pipelines handle the ingestion, normalization, and storage of time-series sensor data at the volumes a multi-room vertical farm generates.
Built for vertical farms that have accumulated sensor data across multiple systems and need a unified data layer before analytics, forecasting, or automation investments will pay off.

03 Buy, build, or wait

The vertical farming question is really about whether the software understands growing.

Buy or rent

Off-the-shelf CEA platforms, while you fit
Standard crop mixes and facility layouts before the non-standard rooms, the tariffs, and the traceability needs outgrow the assumptions.
Generic ERPs, as a bridge
Manufacturing ERPs that don't understand growing cycles. Honest for finance, wrong for the grow.

Build custom

When the data doesn't connect
$2M of equipment and harvest weights in a Google Sheet. You can't optimize what you can't measure.
When the knowledge is in one head
One resignation away from losing years of operational learning. The recipe becomes the system's.
When energy is the margin
Every photon has to be paid for. Cost-per-kilogram by room and shift, or guesswork.

Bottom line

Stay on the platform while the crop mix and the facility fit its assumptions. Build when the data, the knowledge risk, or the energy economics outgrow it.

04 How we work

How we build vertical farming software

01
Discovery
Two to three weeks mapping your grow operation. We document the sensor systems and control infrastructure in place, the data that exists and where it lives, and the operational workflows your grow team follows. We surface the business decisions your management team cannot make well because the data is not connected. The risk this retires: the requirement discovered at harvest.
02
Design and data architecture
We design the data model around your operation: the batch record structure, the time-series schema for sensor telemetry, the integration points with existing SCADA, ERP, or IoT infrastructure, and the API surface that connects everything. Prototypes of the key workflows are reviewed with your grow team and operations managers before build begins. The risk this retires: the data model that can't express the grow.
03
Build
Two-week sprints with working software at each checkpoint. The core data integration and monitoring layer ships first, so your team can see live data in the new system while remaining capability areas are built. Grow-cycle management, forecasting, and energy analytics follow in sequence. The risk this retires: the integration that fails at harvest scale.
04
Handover and iteration
Go-live runs in parallel with existing systems for two to four weeks until your team is confident in the new data and your grow records confirm accuracy. We deliver documentation and admin access as part of the handover. The risk this retires: the cutover that loses the crop.

05 Track record

What vertical farming businesses get when they work with us

Weeks to a validated v1, then grow the full platform: 12-16

Shipping production software across food, agriculture, and operations: Since 2015

Cost agreed before development starts: Fixed

08 Why us

Why choose us?

01
We've seen your problem before
Across dozens of industries, we recognise your situation fast, then frame the fix around your margin and your operations, not a generic template.
02
We own the number, not the ticket
We measure success the way you do: hours saved, revenue earned, margin recovered. We stay through launch and growth, so the result is ours to own.
03
Serious businesses trust us
Vodafone, T-Mobile, Cisco, Energia, Aldi, Nike. Building since 2015. Serious businesses keep coming back because we stay accountable long after launch.

09 Questions

Common questions

: Yes. Most vertical farm builds we scope involve integrating with existing SCADA, PLC, or BMS infrastructure rather than replacing it. We connect to your existing control layer via OPC-UA, MQTT, or Modbus protocols, pull real-time telemetry into a unified data platform, and build the analytics, alerting, and planning tools on top. Your grow team keeps the control interface they know; you gain the data layer you need.
: Yes. Yield forecasting for vertical farms is crop-specific and environment-specific, which is why generic agriculture software tools produce forecasts with wide error bands. We build forecasting models trained on your historical grow data, factoring in your cultivars, lighting schedules, nutrient programs, and room-level climate variables. The output is a forecast your sales team can commit to, with confidence intervals that narrow as the harvest date approaches.
: A first module (a climate monitoring platform or a grow-cycle tracking system) launches as a validated v1 in about 12 to 16 weeks. You grow it from there. A full operations platform covering climate control integration, grow-cycle management, yield forecasting, energy dashboards, and harvest planning runs 18 to 28 weeks of build. Cost depends on the number of sensor integrations, grow rooms, and forecasting complexity, and is fixed before development starts.
: Yes. We build integrations with AWS IoT Core, Azure IoT Hub, and direct MQTT broker connections from sensor hardware including Modbus-based environmental sensors, CO2 monitors, and smart lighting controllers. If your hardware already sends data to a cloud endpoint, we connect to that stream. If it does not, we scope the IoT gateway layer as part of the project.
: Off-the-shelf vertical farming platforms work well when your crop mix, facility layout, and operating model match the assumptions the platform was built around. Custom development becomes the right choice in four cases. Your facility has non-standard grow-room configurations. You sell into channels that require specific traceability reporting. Your energy tariff structure needs optimization logic the platform does not support. Or the platform's per-seat pricing becomes a constraint as you add grow rooms. We scope what needs to be custom versus what can use an off-the-shelf component during discovery.
: Yes. Grow team workflows (batch record entry, environmental spot checks, pest and disease logging, transplant confirmations) are best captured on a mobile device at the point of work rather than typed up later at a desktop. We build iOS and Android apps, or React Native cross-platform apps, that work offline inside the facility and sync to the central system when connectivity is restored. Offline-first design is a requirement for in-facility mobile tools, not an optional extra.
: This is the single largest institutional risk for growing operations. When crop recipes, environmental adjustment strategies, and troubleshooting intuition live exclusively in one person's head, you're one resignation away from losing years of operational learning. We build grow-cycle management that captures the recipe as data: every batch records the cultivar, the lighting schedule, the nutrient program, and the environmental history. The knowledge becomes the system's, not the resignation letter's.

Vertical farming software by product

Get a build-vs-spreadsheet plan for your facility

Tell us your crops, your grow rooms, and the decisions you can't make because the data isn't connected. We'll tell you what we'd build, what it costs, and what we'd leave alone.

Scope and cost agreed before work starts. No surprises. No obligation.
Working prototype within 3 weeks of kickoff.
Pay by milestone. You see progress before each invoice.
60-day post-launch warranty. Bug fixes, UI tweaks, and deployment support. No retainer.
All conversations are NDA-protected.

Your name

Your work email

Please enter a valid email address.

Your phone number