Start a conversation Applied AI · Botswana
Responsible decision-support for livestock, climate and health—built for the realities of African operating environments.
Built in Botswana. Designed for scale.
AIgentIQ turns complex operational challenges into practical, responsible AI products. Our work begins with the people, evidence, institutions and safeguards required for a solution to function in the real world.
We focus on high-impact domains where better evidence and earlier action can strengthen livelihoods, public services and institutional decision-making.
Portfolio in development
Each solution applies a shared discipline: local relevance, measurable evidence, human oversight and responsible data use.
Agriculture & livestock
An agriculture and livestock intelligence platform whose first module, EACS, supports early screening of visible FMD-like and LSD-like cattle concerns. Guided smartphone capture produces a non-diagnostic AI risk flag and structured case report for faster veterinary review and follow-up.
Climate-aware livestock health
A Botswana-focused reporting and veterinary-escalation workflow combining structured farmer observations, controlled image screening and real district-level environmental context.
Climate & public health
Botswana-focused climate-health intelligence combining rainfall, temperature, vegetation, surface-wetness, population and health-access indicators. It helps identify malaria and mosquito-breeding conditions while tracking excess heat, heavy rainfall, flood potential and drought-related stress.
Applied AI development
We work from a defined problem through feasibility, data readiness, responsible-AI controls, prototyping, evaluation and a credible implementation pathway.
Responsible by design
We treat responsible AI as an engineering and operating requirement—not a statement added at the end.
Define who acts, what evidence they need and where AI can genuinely improve the workflow.
Assess availability, consent, quality, representativeness and ground truth before making performance claims.
Design clear oversight, escalation, uncertainty and accountability into high-stakes workflows.
Measure field usefulness, safety, adoption and operational reliability—not only model accuracy.
FarmSight · EACS
EACS—Early AI Cattle Disease Screening—guides farmers and field agents through structured smartphone evidence capture, generates a non-diagnostic AI risk-support flag and prepares a case for veterinary review.
Prompts help users collect more consistent images of visible cattle-health concerns.
Relevant case metadata, observations, location context and consent travel with the evidence.
A non-diagnostic AI flag supports prioritisation and communicates limitations.
A structured evidence report helps a veterinary professional review and respond.
Internal prototype evidence
These limited internal tests establish technical feasibility—not clinical validity or field performance.
11 false negatives · 2 false positives
2 false negatives · 0 false positives
PulaVet Link · Botswana
PulaVet Link demonstrates how a farmer's observation can become a structured, climate-aware veterinary handoff. Synthetic livestock cases are paired with observed 2025–2026 environmental context and a controlled, non-diagnostic cattle-image workflow.
Record visible signs, herd context, movement, water, grazing, heat observations and consent.
Preview a consented image locally through a scripted LSD-like or oral FMD-like evidence pathway.
Attach rainfall, vegetation, heat and static water context against a transparent 2015–2024 project baseline.
Apply conservative warning-sign rules and prepare a downloadable veterinary handoff.
Build the evidence with us
01Domain and research partners
02Pilot sites and implementation institutions
03Funders and responsible investors
04Technical and data collaborators
Founder & project lead
A Botswana-based technology and strategy professional with a foundation in Computer Engineering, an Executive MBA and ongoing doctoral work focused on emerging technologies and Generative AI. Mahatma brings experience across applied AI, product development, business strategy and stakeholder-led programme delivery.
Partnerships · Pilots · Investment