Based in
Nairobi, Kenya
About me
I’m Genson Kithome
I build the infrastructure behind clearer decisions.
I build the data and automation infrastructure that agrifood businesses and SMEs don’t yet have. That’s what Spirdlytics is—SQL pipelines, Power BI dashboards, and automated reporting systems that replace manual data entry with real-time operational visibility.
Where this comes from
The ground I learned to read first.
Agrifood isn’t a market I picked. It’s the terrain I grew up reading.
I’m from Tharaka, one of Kenya’s drylands counties: unpredictable yield, thin margins for error, and decisions made on incomplete information because the data infrastructure to do otherwise simply doesn’t exist. That’s the problem I’ve spent my career building tools against.
The build so far
Built from the ground up.
Each step added a layer: accountable collection, quality discipline, operational analysis, working systems, then a practice built to do it for others.
2019
Census Enumerator
Kenya National Bureau of Statistics
Field data collection across Tharaka during a national statistics exercise—my first exposure to structured, accountable data work.
Field collection2020
Data labelling & annotation
Remotasks
High-volume dataset labelling and annotation at 95%+ accuracy against strict QA standards. This is where data-quality discipline became part of how I work.
95%+ accuracy2023–2024
Product Development Analyst
Haraka Tutors
Analysed operational and delivery data to identify workflow bottlenecks and sustain a 99.4% on-time delivery rate. Demand forecasting informed service and staffing decisions, while automated evaluation tools lifted processing efficiency by 35%.
99.4% on time · 35% lift2024–2026
From raw logs to live operations
Spird Farms
Four roles, one continuous arc: auditing agricultural logs, standardising livestock and crop records, building interactive dashboards and feed-optimisation models, then deploying a Milk Ordering & Distribution Portal that improved delivery-fulfilment tracking by 40%.
40% tracking improvement2026
Founder
Spirdsheet Automations
The shift from solving this problem inside one operation to solving it for many—SQL pipelines, Power BI dashboards, and spreadsheet automation for SMEs, startups, and agrifood operators that need decision-ready data without hiring a data team.
Built to scale
How I work
A sequence that keeps dashboards from becoming decoration.
It isn’t a template. It is the discipline that turns raw records into decisions.
- 01
Business context
Start with the operation and the decision that needs to improve.
- 02
Data understanding
Read the records, systems, gaps, and quality issues before building.
- 03
Meaningful KPIs
Define measures that reflect how the business actually performs.
- 04
Analysis
Interrogate the data for patterns, causes, risks, and opportunities.
- 05
Action
Turn the findings into recommendations the business can use.
The FruitCo SQL analytics build and Mimea FoodMart demand-vs-discount deep dive follow this discipline end to end.
See selected workDirection, not completed work
Where this is going: 2026–2030.
A four-phase direction for turning an analytics practice into durable agrifood intelligence infrastructure.
Phase 1 · 2026
Foundation built
Spirdsheet Automations becomes a repeatable analytics and automation practice, backed by ALX data engineering and data science training. Clients get dashboards, SQL pipelines, and spreadsheet automations that replace manual reporting.
Phase 2 · 2027
Market intelligence live
Agriflow Insight launches as a regular agrifood intelligence product. Clients get curated market, operational, and pricing signals they can act on faster than competitors.
Phase 3 · 2028–2029
Predictive layer
Machine learning and data engineering are layered onto the analytics base. Clients get forecasting, anomaly detection, and automated workflows that move from what happened to what happens next.
Phase 4 · 2030
Agrifood expert partner
By 2030 the practice combines 4+ years of data analytics, engineering, and ML with a BSc Agriculture background. Clients get a partner who speaks both agrifood operations and data fluently.
The bet
Africa’s agrifood sector isn’t short on opportunity. It’s short on infrastructure.
The systems that turn raw operational data into decisions made with confidence—that’s the layer I’m building, starting from the ground I know best.
Reliable data
Visible operations
Better decisions
If you’re an SME, startup, or agrifood operator running on spreadsheets, gut instinct, or disconnected tools, I can build the dashboard and automation layer that closes that gap.