Cyber criminals don’t target the world’s largest enterprises exclusively. In fact, 94% of small and mid-sized businesses find themselves a victim of at least one cyberattack in 2024; and that covers everything from opportunistic phishing to full-scale breaches.
Each attack carries a financial sting. Researchers found ransomware attacks cost organisations over £615 million in 2024, with average payments hitting £2 million. For a small firm, that can have a detrimental impact on whether or notthe company stays open for business. A 2025 Mastercard survey found that nearly one in five small businesses that suffered an attack then filed for bankruptcy or closed their business entirely. The reality of the threat landscape is that SMBs face the same level of increasingly sophisticated attacks, with fewer staff and thinner safety nets.
Cybercriminals continue to exploit smaller teams working with tight budgets and ageing systems. Beyond knowing the risks, SMBs need to tackle the core factors that leave them exposed—namely, limited staff, limited time and technology stacks that lag behind modern threats. Larger companies can absorb fines, pay ransoms or invest in bespoke AI solutions, but smaller companies can’t. They need tools that stretch every pound and help them move faster without increasing risk.
Why RAG makes sense for smaller security teams
AI is everywhere in the security conversation, but building custom models requires significant spend and staffing. Retrieval-Augmented Generation (RAG) offers a more grounded option. Instead of pulling information solely from LLMs that are more likely to guess or hallucinate, RAG systems retrieve verified information from trusted sources (internal or external) before generating a response. For a busy IT manager or small cyber team, this means instant access to internal documentation, threat intelligence and incident-response playbooks without exposing private data to open models.
Until recently, RAG was something only large enterprises could afford to experiment with. Building retrieval pipelines, maintaining vector databases and tuning models required deep technical investment. RAG-as-a-service has broadened accessibility by delivering the same capabilities through a secure, scalable SaaS platform. In turn, smaller organisations can adopt advanced AI without having to build or manage it themselves.
This levels the playing field. Still, a retrieval system can only surface what you feed it, so keeping internal material current matters as much as the technology itself. Rather than wrestling with model tuning, teams can focus on leveraging AI-driven insights to strengthen their defences and analyse large security data sets—tasks that previously demanded expert-level skills. Best of all, they can do so in an environment that provides built-in security and compliance frameworks which would be difficult for smaller teams to replicate. In short, with lower infrastructure costs, teams can focus on using AI insights instead of attempting to integrate AI.
Governance: the part SMBs can’t ignore
As with any AI technology, adoption and use requires discipline and strict governance. RAG-as-a-Service providers should mirror the safeguards SMBs expect from all systems: strong encryption for all data transfers, clear separation between customer environments and transparency into how information is retrieved and stored. Should data sovereignty come into play, it must be verified that providers can host and process data in compliant regions.
Beyond strong governance practices, auditability is essential when using RAG. Every query and output generated should leave a visible trail that can be reviewed for accuracy and compliance. This transparency is beneficial on multiple fronts. From a direct audit standpoint, this satisfies regulations such as GDPR, HIPAA and SOC 2. A good audit log becomes a feedback loop, highlighting outdated documents and improving the accuracy of that the model retrieves.
RAG for teams with zero room for error
Not all risks are created equal. For organisations that handle sensitive data, like financial records, patient health information or government contracts, consequences rachet up quickly and severely. This makes updated and strong defences even more crucial. SMBs in these sectors are working with thin margins of error, where a single compliance violation or data breach can be both financially and reputationally devastating. RAG-as-a-Service offers these businesses a way to harness the power of AI while maintaining regulatory alignment. It provides access to enterprise-grade security, encrypted retrieval and comprehensive auditability without the overhead of custom engineering.
For years, cybersecurity has been an uneven contest. Large enterprises have entire security operations centres staffed around the clock, while SMBs rely on overextended teams juggling multiple priorities. With democratised RAG, the host of possibilities is transformational. In finance, regional banks could use RAG-based retrieval to surface regulatory updates in real time and reduce any lag in compliance. Healthcare clinics can quickly reference internal protocols and security documentation without risking exposure of patient information. In government applications, contractors can query project files within a safe and protected environment, maintaining that classified or sensitive materials never leave approved environments. Without the same overhead investment, RAG-as-a-Service enables smaller organisations to meet the same standards as their enterprise counterparts.
A better way to strengthen SMB security
RAG-as-a-Service bridges the divide SMBs face in balancing innovation and compliance by combining the speed and context of generative AI with the assurance of regulated data management; this enables small and midsize businesses to detect threats faster, comply more confidently and compete more effectively, all without massive investment or risk exposure. By serving as an immediate, expert resource, RAG indexes everything from SOC 2 documentation and internal policies to legacy incident reports, safeguarding every answer is grounded in verified facts rather than guesswork. Lean security teams can pose questions such as, “Does our data retention policy align with the latest GDPR requirements?” and receive prompt, referenced responses, thereby streamlining compliance research, reducing human error and enabling regulations to be mapped directly to operational controls. With SaaS-based retrieval platforms, organisations of any size gain audit-ready insights and pinpoint accuracy, empowering growing businesses to remain secure and compliant without incurring the substantial costs of traditional, enterprise-grade platforms.
Richard Barretto
Richard Barretto is Chief Information Security Officer at Progress, a software company that provides high impact software for 70% of fortune 500 companies and 4 million plus developers. Richard leads all aspects of Progress’ enterprise cybersecurity practice, delivering the vision and strategy, and governance against a churning landscape of digital threats. .
