About SoJen.AI
Communication intelligence that works before the damage compounds.
SoJen.AI is a communication intelligence platform built around a patent-pending transformer methodology for detecting implicit language risk before content is sent. The B2B API gives enterprise organizations in HR, trust and safety, education, and regulated industries a structured way to identify escalation signals, document risk patterns, and demonstrate proactive governance — at 98% F1 recall, on the language that keyword filters consistently miss.
Our Approach
A Different Problem Than Traditional Moderation Solves
Most moderation systems are built to remove harmful content after it has been reported. By then, the conversation has already escalated, the screenshot already circulated, the regulatory clock already started. SoJen.AI was built for a different intervention point: before the message is sent.
The harder problem is not identifying explicit threats — that is largely solved. The harder problem is detecting the escalating tone, the coded language, the implicit framing that creates legal exposure and organizational harm without triggering a single keyword filter. That is where SoJen.AI’s patent-pending transformer methodology operates.
The current enterprise API is the first product built on this methodology. The longer-term SoJen.AI vision is embedding this detection layer directly into communication platforms — so that intelligent, proactive intervention is the default, not an afterthought.
Pre-Publish Detection
Intervention at the moment of authorship — before content is sent and before damage occurs.
Implicit Risk Detection
98% F1 recall on escalating tone, loaded framing, and coded language — the patterns keyword filters miss.
Documented Governance
Every detection event creates an audit trail — proactive risk management that regulators, HR teams, and legal counsel can act on.
Celia Banks, Ph.D.
Founder & Chief Scientist
About the Founder
Built by a researcher who studied the problem before building the solution.
Dr. Celia Banks is a data scientist and published researcher whose work sits at the intersection of language, bias, and organizational communication. The research question that became SoJen.AI was formalized during Dr. Banks’ Masters in Applied Data Science at the University of Michigan: how can machine learning and artificial intelligence be applied to detect and mitigate harmful language patterns in ways that general NLP tools cannot? The capstone project built the first version of the models. The commercial platform is what you get when you combine that research foundation with twenty years of knowing how to build AI systems that actually scale.
Dr. Banks came to that research question through an unusual path. She honorably served in the U.S. Air Force. She held senior roles at Bristol-Myers Squibb and Pfizer, and led large-scale program delivery at Oracle Corporation. She founded I-Meta, a Big Data analytics company where she developed and patented the Spice Chip Technology system. SoJen.AI’s pending patent is her second — a track record of building technology defensible enough to protect.
Her doctorate from Fielding Graduate University in Human and Organizational Systems provided the foundational insight: harmful language is not just a linguistic pattern. It is a behavioral and organizational pattern — one that propagates through systems in ways that require understanding of human dynamics, not just NLP architecture. That understanding is what makes SoJen.AI’s models detect what other tools miss.
The combination is specific and difficult to replicate: a patented inventor’s understanding of scalable data infrastructure, a data scientist’s model-building expertise, and a behavioral scientist’s understanding of how communication risk actually travels through organizations and platforms. No other team in this market holds all three.
SoJen.AI is not a general-purpose AI safety tool. It is a focused, domain-specific system designed by a researcher who has worked on the underlying science of measuring communication risk—not simply detecting it—and who understands what organizations actually need when communication becomes a organizational, governance, legal, or human consequences question.
Mission
Mission, Vision, and Approach
Mission
Give organizations the technical capability to detect and document communication risk before it escalates — transforming proactive governance from a goal into a measurable, auditable practice.
Vision
A future where communication platforms catch implicit risk before it compounds — where intelligent intervention is embedded into the moment of authorship, not bolted on after the fact.
Approach
Patent-pending transformer models trained on the language patterns that matter — combined with organizational context, custom lexicons, and human-centered intervention design — to deliver detection that is accurate, explainable, and defensible.
Differentiation
Not competing with AI infrastructure. Operating above it.
SoJen.AI is not an AI safety API of the kind AWS, Azure, or Google provide. Those are infrastructure services. SoJen.AI occupies a different position in the stack: a domain-specific communication intelligence layer that sits above general-purpose NLP services and below the enterprise workflows where language risk actually creates consequences. The distinction matters — because an infrastructure API trained on general content does not know what implicit escalation looks like in your industry, your HR environment, or your user population.
Applications
Where SoJen.AI Applies
Enterprise Communication Risk
Support organizations in identifying, documenting, and mitigating language risk across digital channels — before escalation creates legal, reputational, or human consequences.
HR and Employee Relations
Give HR leaders a consistent, defensible process for evaluating communication risk in workplace environments — with an audit trail that demonstrates due diligence.
Education and Regulated Environments
Detect early warning signals in K-12 and higher education settings where communication risk has direct safety, legal, and institutional consequences.
Trust, Safety, and Platform Integrity
Help trust and safety teams catch implicit escalation patterns before they become moderation incidents — reducing cost, response time, and reputational exposure.
Built for organizations that need more than reactive moderation.
If your organization is evaluating what a proactive, documented approach to communication risk management looks like — and whether SoJen.AI is the right fit for your environment — the discovery conversation is where that starts. Engagements are scoped individually; there is no pricing page because there is no standard configuration.