Reduction in due-diligence time
Since founding in early 2025
Team members across product, engineering, ML, and compliance
Core product modules
At the heart of ClarigenAI is a plug‑and‑play architecture that connects diverse data sources (structured and unstructured), orchestrates custom pipeline logic, and delivers outputs that balance speed, accuracy, and interpretability.
Designed to revolutionize financial and compliance workflows with automated parsing of financial statements, legal analysis, behavioral indicators, and alternative data layers.
Deliverables include: Risk heatmaps, summarized intelligence reports, forward-looking forecast signals, and drill-down dashboards for further exploration.
ClarigenAI is actively evolving into a flexible intelligence layer built to navigate high-complexity decision environments. Our AI tools are expanding in scope through purpose-built modules:
Shortened due‑diligence cycles, automated risk flags, and comprehensive company profiles—integrating financial, legal, and behavioral signals for early-stage assessment and deal qualification.
Real-time and retrospective monitoring of executive behavior, litigation history, governance practices, and regulatory exposures—enabling organizations to manage risk proactively.
Synthesizing ESG signals, executive communication trends, and behavioral patterns to assess long-term sustainability, organizational integrity, and reputational alignment.
AI-powered insights into legal, financial, and reputational risk that inform underwriting models, exposure mapping, and strategic planning.
Supporting teams analyzing dense technical documents, historical filings, and compliance frameworks—helping reduce manual overhead while improving interpretability and consistency.
Shortened due‑diligence cycles, automated risk flags, and comprehensive company profiles—integrating financial, legal, and behavioral signals for early-stage assessment and deal qualification.
Real-time and retrospective monitoring of executive behavior, litigation history, governance practices, and regulatory exposures—enabling organizations to manage risk proactively.
Synthesizing ESG signals, executive communication trends, and behavioral patterns to assess long-term sustainability, organizational integrity, and reputational alignment.
AI-powered insights into legal, financial, and reputational risk that inform underwriting models, exposure mapping, and strategic planning.
Supporting teams analyzing dense technical documents, historical filings, and compliance frameworks—helping reduce manual overhead while improving interpretability and consistency.
KarmicDD connects to diverse data sources including financial statements, legal filings, news articles, regulatory databases, and proprietary client data. Our ingestion layer handles both structured formats (APIs, spreadsheets) and unstructured documents (PDFs, Word docs) with automatic parsing and normalization.
Our hybrid processing engine combines advanced NLP models, financial analytics, and domain-specific rule engines. Key components include: anomaly detection for financial irregularities, contract clause extraction, entity relationship mapping, behavioral signal analysis from communications, and ESG compliance scoring.
Unlike generic analytics tools, KarmicDD applies domain-specific reasoning to identify meaningful patterns. Our models understand financial contexts, legal frameworks, and behavioral norms to surface truly relevant risks rather than noise. Each finding is scored for confidence and includes full audit trails.
Results are delivered through multiple interfaces: executive dashboards with risk heatmaps, detailed investigation reports, customizable alerts, and API integrations. Every insight includes explainability features showing why it was flagged, what data sources contributed, and confidence levels.
Every development sprint begins with a real-world question or pain point. We iterate quickly—from prototype to feedback loop to refinement. That feedback is rooted in actual workflows—whether they come from financial teams, compliance departments, or technical infrastructure operators.
We train, test, and validate models using real datasets. That includes historical filings, risk data, public legal records, and actual client inputs. No made-up models, no synthetic-only baselines. Our models are measured in the same environment in which they operate.
Each model layer embeds traceability: why a risk flag was raised, which data source influenced the classification, and how confidence was determined. Audit logs and model lineage are built in—not bolted on.
ClarigenAI is cloud-native, with zero-trust architecture, encryption-at-rest/in-transit, and role-based access controls. We support white-label deployment, air-gapped environments, and private-cloud options for sensitive operations.
Purpose-built large language models that parse long-form documents—such as investor agreements, regulatory filings, and corporate disclosures—to extract key clauses, red flags, and compliance indicators.
Intelligent linking of people, organizations, and financial/legal signals to uncover hidden affiliations, patterns of control, and potential conflicts of interest.
Natural language pipelines that analyze communication tone, thematic consistency, and behavioral cues—helping surface reputational and cultural risk buried in unstructured content.
End-to-end models that combine structured financials with unstructured data (PDFs, news, filings, public statements) to generate risk scores, summaries, and investigative dashboards.
Each module is purpose-built to augment human expertise, not replace it—giving analysts, compliance officers, and investors faster, clearer insights with full auditability and control.
Brings deep expertise in corporate compliance, financial oversight, and regulatory governance—having worked closely with boards, legal teams, and CA-certified institutions to ensure operational integrity across numerous organizations. Former corporate director and CA-certified examiner with over a decade of board-level experience.
Shaped by hands-on experience in backend systems, generative AI applications, and modular machine learning architectures. Passionate about solving problems at the intersection of finance and real-world data complexity with a unique combination of engineering skill and relentless curiosity.
ClarigenAI's story begins with a simple premise: what if AI wasn't just intelligent, but context‑aware? What if it could reason not only with data, but also with structure—financial governance, legal frameworks, and behavioral signals embedded in real-world decisions?
Behind ClarigenAI are founders from two deeply complementary worlds. One brings deep expertise in corporate compliance, financial oversight, and regulatory governance—having worked closely with boards, legal teams, and CA-certified institutions to ensure operational integrity across numerous organizations. With a strategic mindset and a sharp lens on risk, this founder recognized a gap in how decision-makers struggle to unify fragmented due-diligence processes.
The other is a curious and driven technical mind—shaped by hands-on experience in backend systems, generative AI applications, and modular machine learning architectures. Passionate about solving problems that sit at the intersection of finance and real-world data complexity, this technical founder anchors ClarigenAI's product vision with a unique combination of engineering skill and relentless curiosity. Constantly experimenting, iterating, and learning, their energy fuels the agility and adaptability of our platform.
What started as a set of conversations about inefficiencies and missed insights quickly turned into a conviction—that the world doesn't need more generic AI. It needs intelligence that understands context, earns trust, and actually helps professionals make smarter decisions in dynamic environments.
ClarigenAI was built from this belief. Not to replace human judgment, but to amplify it—through systems that are as explainable as they are powerful.
ClarigenAI operates like a tight-knit core team—not a bloated org chart. We're small by design (fewer than 15 people across product, engineering, ML, and compliance) and fast by choice. That means high ownership, rapid decision-making, and direct access to leaders at every level.
Every feature must deliver measurable value. We measure impact, not activity.
We go deep—on latency, accuracy, feature explainability, and reliability.
Compliance is built-in. Every insight is provable—and auditable.
We publish postmortems, host "show-and-tell" sessions, and celebrate learning—especially from failures.
We bring in complementary skill sets—finance, compliance, ML, engineering—to challenge assumptions and broaden perspective.
While still early stage, our early deployments tell a consistent story:
70% reduction in due-diligence cycle time for pilot clients.
Significantly improved risk visibility—clients catch red flags earlier, across legal, financial, or behavioral domains.
High user satisfaction—direct access to builders ensures tight partnerships and rapid issue resolution.
Compliance-first credibility—our governance strategist brings over a decade of board-level experience, earning trust from cautious, high-regulation environments.
ClarigenAI's north star is to become the trusted AI intelligence layer for regulated, high-stakes industries. Over the next 3–5 years, we aim to:
Traditional tools analyze data in isolation—ClarigenAI reasons with structure, risk norms, and behavioral context baked into its pipeline.
Rather than trading off velocity for accuracy, we deliver both. KarmicDD turns months into minutes—without compromising nuance or auditability.
From audit logs to regulatory tracing and permissions management, every output is traceable and defensible.
Each module—from due-diligence to anomaly detection—is plug-and-play. Use only what you need, scale as you grow, and integrate with existing systems.
While many startups pivot or chase flash trends, we stay focused on vertical fusion: finance, compliance, deep‑tech, hybrid ML. That gives us clarity—and compounding expertise.
Feature attribution, audit trails, decision lineage and confidence scoring for every insight.
Cloud-native, zero-trust architecture, encryption-at-rest/in-transit, and role-based access controls.
Every output is traceable and defensible with full regulatory tracing and compliance alignment.
Each module—from due-diligence to anomaly detection—is plug-and-play for flexible integration.
Join our pilot program and experience the future of contextual AI intelligence. ClarigenAI is built for early adopters who want more than analytics—they want answers, not just estimates.