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AgriTechFounder venture

TerraGrow

AI and data infrastructure for controlled-environment agriculture.

Led TerraGrow as a founder/operator, building agritech data systems that connected AI, IoT, cultivation intelligence, dashboards, and business operations.

Role

Founder, CTO, product and engineering leader

Timeline

April 2021 - Present

Users

3M+ daily data points processed

AgriTechIoTAI AnalyticsData InfrastructureTeam ScalingFundraising
OverviewGalleryArchitectureMore Work

$2M

Venture-backed execution

3M+

Large-scale agritech telemetry

40+

Engineers led across teams

Built agritech data systems for high-volume operational telemetry.

Connected product strategy, fundraising, technical architecture, and team growth.

Translated complex cultivation workflows into dashboards and decision-support systems.

Problem

What was broken or inefficient?

Controlled-environment agriculture produces massive operational data, but teams need actionable intelligence rather than raw telemetry.

Solution

What Mohammed built

TerraGrow organized agritech data into platform workflows that supported operations, insight, and executive decision-making.

Execution

What Mohammed built to move the product forward.

TerraGrow organized agritech data into platform workflows that supported operations, insight, and executive decision-making.

High-volume telemetry pipelines

Operational dashboards

AI-assisted cultivation intelligence

Cloud-hosted data systems

Team scaling and delivery operations

Stakeholder and investor-facing product narrative

Technology signals

IoT dataAnalytics dashboardsCloud infrastructureOperational data modelsTeam leadership

Execution Surface

Core modules and product decisions

The strongest work sits at the intersection of product judgment, technical architecture, and operating constraints.

Technology Signals

IoT dataAnalytics dashboardsCloud infrastructureOperational data modelsTeam leadership
01

Built agritech data systems for high-volume operational telemetry.

02

Connected product strategy, fundraising, technical architecture, and team growth.

03

Translated complex cultivation workflows into dashboards and decision-support systems.

04

Scaled technical teams and delivery operations during venture growth.

01

High-volume telemetry pipelines

02

Operational dashboards

03

AI-assisted cultivation intelligence

04

Cloud-hosted data systems

05

Team scaling and delivery operations

06

Stakeholder and investor-facing product narrative

Outcomes

  • Raised venture funding while building the underlying technical platform.
  • Processed data at a scale that made architecture and observability core product concerns.
  • Built leadership proof across product, engineering, and business execution.

Lessons

  • Founder-led technology work requires architecture that can survive both demos and operations.
  • Data platforms become valuable when they change daily decisions for operators.

Recruiter Takeaway

Mohammed brings founder-level ownership: he can raise, hire, architect, ship, and translate complex systems into business outcomes.

Architecture

How The System Holds Together

These are public-safe architecture layers: enough to show leadership judgment without exposing sensitive implementation detail.

01

Telemetry Backbone

Agriculture signals are modeled for operational analysis rather than passive reporting.

02

Scalable Platform

Cloud architecture supports high-volume ingestion, dashboards, and system growth.

03

Founder Execution

Technology decisions were tied to hiring, fundraising, demos, and business milestones.