years across enterprise data, reporting, software, automation, and standards
Founder Profile
Somia Jamal
Founder of Somiphy · Standards-First Data Intelligence · Product Data Intelligence · Observational Intelligence · Responsible AI
"AI does not begin with a model. It begins with trusted data."
Somia Jamal is the founder of Somiphy. She has 20+ years of experience in enterprise data, software development, business intelligence, and data standards.
Much of her career was shaped by her work at GS1 Canada. There she worked in data architecture, vendor compliance, and data quality. She built dashboards, APIs, and tools used by retailers, manufacturers, and industry partners.
Her experience includes supporting data-driven ecosystems connected to major retailers, manufacturers, and CPG organizations, including Loblaw, Costco, Sobeys, Procter & Gamble, Unilever, Nestlé, and 3M Canada.
Through Somiphy, Somia helps organizations turn messy, fragmented data into trusted intelligence. She does this through data governance, dashboards, automation, and responsible AI.
Personal Mission
Somia's personal mission is rooted in road safety. She believes human observation, trusted data, and AI can identify risk before harm occurs. Somiphy turns those observations into reports, dashboards, and action signals. The goal is safer roads and stronger communities.
background in GTIN analytics, vendor compliance, data quality, and product data ecosystems
focused on responsible AI, trusted data foundations, dashboards, and action signals
Flagship Use Case: CRSIF Road Safety Intelligence
A standards-first intelligence model applied to road safety.
CRSIF — the Canadian Road Safety Innovation Foundation — is one of Somiphy's most meaningful projects. It uses AI, observational data, compliance scoring, and predictive dashboards. The goal is to help communities spot road risk before incidents occur.
CRSIF is a flagship project of Somiphy's standards-first intelligence model. Somiphy is not a road-safety-only company. It applies the same data discipline to retail, operational, and observational data ecosystems.
HO
Human Observation Systems
Structured forms and workflows to collect real-world behavioural observations at intersections and road environments.
IR
Intersection Risk Intelligence
Geospatial and time-based signals that help communities understand repeated risk patterns before harm occurs.
AV
AI Validation Engines
Anomaly detection and data quality checks to protect the integrity of observational road safety data.
SC
Compliance Scoring
Standards-based scoring models that convert observations into clear, comparable road safety compliance indicators.
DB
Predictive Dashboards
Modern visual intelligence for municipalities, nonprofits, government partners, schools, and community stakeholders.
RP
Risk Pattern Detection
AI-assisted identification of recurring behavioural risk, compliance gaps, and early warning signals.
SR
Standards-Based Reporting
Clear reporting frameworks that support consistency, accountability, transparency, and decision-making.
AR
Action Action Signals
Translating intelligence into practical safety interventions, policy support, and community action.
Human-Interface Intelligence
Where observation meets AI.
Modern road safety cannot rely on awareness alone. It needs standards, data, AI, and human observation. These tools can identify risk before something goes wrong.
Human Context
Human observation captures behaviour, context, judgement, and real-world risk that traditional systems often miss.
AI Intelligence
Artificial intelligence helps validate submissions, detect patterns, surface anomalies, and transform observations into early warning signals.
Prevention Focus
The goal is not only to report what happened. The goal is to identify risk, guide action, and help save lives on the road.
Why Somiphy
A rare blend of standards, software, and intelligence.
Somiphy is different because it combines data standards expertise with AI, software engineering, and real-world compliance thinking.
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Deep data standards expertise
A standards-first foundation for trusted systems and reliable intelligence.
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AI and modern software engineering
Purpose-built platforms, APIs, automation, dashboards, and intelligent workflows.
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Real-world compliance knowledge
Systems designed for accountability, auditability, governance, and measurable outcomes.
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Mission-driven innovation
Technology that supports prevention, public value, enterprise trust, and human-centred impact.