AI Advisory for Regulated Industries
Securing the software supply chain beneath community banking.
Cijara Group helps community banks and regulated small businesses adopt AI safely - implementation, security, and governance from practitioners who ran risk programs inside the nation's largest financial institutions.
- 3
- Service Lines
- 15+
- Years in Bank Risk
- NC
- Headquartered
The Problem
The risk you inherit.
Community banks run on software they did not write. Your core banking system, your digital banking platform, and your loan origination tools come from vendors - and all of it rests on open-source software. A single .NET service depends on dozens of packages directly and hundreds more beneath them. You see almost none of it.
That hidden layer is where modern attacks land. Log4Shell showed the pattern: one logging library exposed a large share of the internet, and defenders spent months finding every place it lived. Community banks lived through that scramble without the staff to run it.
Cijara Group gives you sight into this layer - mapping the open-source components inside your systems, showing which known flaws actually reach your environment, and researching the components you depend on for the issues nobody has found yet.
How this maps to examiner expectations →What We Do
Implementation, security, and governance.
Three service lines, one operating principle: adopt AI and modern software without taking on hidden risk - and be able to prove it to your examiners.
AI Implementation
Cijara Group helps small and mid-size businesses in highly regulated industries - community banks above all - put AI to work without losing control of risk. We start from your workflows and your regulatory obligations, not from a vendor demo, and we stay through rollout so the tools actually get used.
Explore service →AI & Software Supply-Chain Security
Your core banking system, digital banking platform, and loan origination tools come from vendors - and all of it rests on open-source software you never see. Cijara Group maps that hidden layer, shows you which known flaws actually reach your environment, and researches the components you depend on for the flaws nobody has found yet.
Explore service →AI Governance & Model Risk
Cijara Group builds the governance layer regulators expect around AI and models - risk frameworks, inventories, testing evidence, and board reporting. Our principal spent 15+ years inside model risk and operational risk functions at major financial institutions, including MRIA remediation under direct regulatory scrutiny. We bring that operator-grade discipline to institutions that cannot staff it full-time.
Explore service →Responsible AI
Governance is the differentiator.
Plenty of firms can stand up an AI tool. Far fewer can hand your board the paper trail that lets a regulated institution deploy it - and defend it. Cijara Group turns Responsible AI obligations into deliverables that close the gap between a technical capability and an approved deployment.
Governance-led, not model-led
We lead with risk discipline and regulatory alignment, then apply AI inside that structure. Regulated businesses need defensible process; the model is the easy part.
Artifacts an examiner can accept
Use-case inventories, risk-management plans mapped to the NIST AI RMF Govern/Map/Measure/Manage functions, model documentation, and human-oversight runbooks - written to survive supervisory review.
Built for regulated environments
Community banks and regulated SMBs face the same expectations as the largest institutions. Our frameworks are calibrated to banking regulatory standards from day one, not adapted after the fact.
Right-sized obligations
Each use case carries only the controls that actually apply, and your team can defend that calibration on review. Governance that slows delivery is governance that gets bypassed.
AI Governance FAQ
What regulators expect on AI.
AI adoption inside a regulated institution is a governance question before it is a technology question. These are the frameworks and expectations that shape a defensible program.
See our AI Governance capability →What is the NIST AI Risk Management Framework?
The NIST AI RMF is a voluntary framework for managing AI risk, organized into four functions: Govern, Map, Measure, and Manage. It is the reference most regulators and examiners recognize for AI risk programs, which makes it the natural backbone for a defensible governance structure.
What do banking examiners expect on AI?
Examiners expect AI use to fit inside your existing risk management framework: a documented inventory of use cases, risk assessments that distinguish inherent from residual risk, effective controls, and board-level oversight. 12 CFR Part 30 (OCC) and Part 364 (FDIC) safety and soundness standards apply to AI the same way they apply to any other material technology risk.
What is ISO/IEC 42001?
ISO/IEC 42001 is the international standard for AI management systems. It defines the policies, roles, and controls an organization should operate to develop and use AI responsibly. It pairs well with NIST AI RMF: the RMF structures risk thinking, 42001 structures the management system.
What counts as a high-risk AI use case?
Any use case whose output materially affects customers, financial decisions, compliance obligations, or the institution's safety and soundness. Credit, fraud, and customer-facing decisions carry the heaviest obligations: pre-deployment testing, ongoing monitoring, human oversight, and documented review. Getting that classification right is what keeps obligations right-sized.
How does a small institution govern AI without a dedicated team?
By right-sizing the program: a use-case inventory, a policy defining acceptable use, risk assessments proportionate to materiality, and a monitoring routine that actually runs. The framework does not need to match a national bank's - it needs to be documented, followed, and defensible.
How does Cijara Group support these requirements?
We lead with governance discipline built inside regulated institutions, then apply AI implementation and security work inside that structure. Deliverables are the artifacts a board or examiner can accept: use-case inventories, risk-management plans mapped to the NIST AI RMF, model documentation, and human-oversight runbooks - sized so your institution carries only the controls that actually apply.
Built for Your Stack
We look where risk concentrates.
Community banks favor a common technical foundation - Microsoft Azure hosting, .NET and C# integration code, Kubernetes, and connections to services like Zelle and digital wallets. Our research targets that environment directly.
- Serialization & data parsingWhere malformed input turns into remote compromise.
- Authentication & token handlingWhere a subtle flaw undermines every login.
- Logging librariesThe source of some of the most damaging supply-chain events on record.
- Outbound HTTP clientsWhere a server-side request flaw exposes internal systems.
Cijara Group is registered under seven NAICS codes. View our codes →
Why Cijara
A partner who speaks both languages.
Most security vendors speak in technical findings a bank has to translate on its own. We deliver findings already framed as risk, mapped to the expectations your regulators hold.
Security depth
SBOM-level dependency inventory, reachability-based triage, and original vulnerability research on the open-source components your operation depends on most.
AI fluency
We pair frontier AI models with experienced analyst judgment - speed and scale in code analysis, with the discipline to separate real findings from noise.
Command of bank risk and regulation
Fifteen-plus years inside model risk, operational risk, and regulatory remediation at major financial institutions. We speak examiner as fluently as we speak engineer.
Findings framed as risk
Deliverables arrive mapped to the expectations your regulators hold and prioritized for an institution with limited staff - no translation required on your side.
Leadership
Joshua Reh - Founder & Principal
Joshua Reh founded Cijara Group after 15+ years inside the model risk, operational risk, AI governance, and enterprise data management functions at major financial institutions - building and operating the programs regulators and internal risk committees rely on.
He leads Cijara's AI implementation, security, and governance work, bringing operator-grade discipline to community banks and regulated small businesses that face big-institution expectations without big-institution staff.
Engage
Start scoped. Start low-risk.
A first engagement is a dependency inventory and known-vulnerability triage of one part of your environment - often the integration layer where your custom code lives. You receive a Software Bill of Materials, a ranked list of reachable vulnerabilities, and clear next steps.
Prefer email? Write us at contact@cijaragroup.com.
Charlotte, North Carolina