Areebi vs Point Solutions (DLP-Only Tools)

DLP-only tools like Nightfall AI and Protect AI emerged to address a real and urgent problem: employees pasting sensitive data into AI chatbots. These tools intercept prompts before they reach an LLM and scan for patterns matching PII, PHI, credit card numbers, API keys, and other sensitive data categories.

Credit where it is due - point solutions do this specific job well. Nightfall AI, for example, uses machine learning-based classifiers to detect sensitive data with high accuracy. Protect AI focuses on model security and adversarial prompt detection. These are legitimate capabilities that solve a legitimate problem.

But DLP is one control in a governance programme that requires dozens. Point solutions answer the question "Is this prompt safe to send?" while ignoring every other governance question an organisation must answer:

• Which AI tools are employees actually using? (Shadow AI visibility)
• Who is authorised to use which models for which purposes? (Access policy)
• Are AI interactions logged for audit and compliance? (Audit trail)
• Can we prove continuous compliance to auditors? (Compliance evidence)
• Where is our AI data processed and stored? (Data residency)
• Can we enforce organisation-specific rules beyond data classification? (Policy engine)

Point solutions answer none of these questions. They are a padlock on one door of a building with fifty unlocked entrances.

The gaps left by point solutions are not minor feature omissions - they are structural governance failures that create measurable organisational risk.

No governed workspace

Point solutions monitor AI usage but do not provide a workspace. Employees still access AI through consumer interfaces (ChatGPT, Claude.ai) or fragmented enterprise tools. This means no centralised conversation management, no document-based RAG, no multi-model comparison, and no administrative control over the AI experience. Areebi's workspace gives employees a better AI experience than consumer alternatives - which is the only reliable way to drive adoption of governed channels.

No policy engine

DLP rules are a subset of governance policies. Organisations also need to enforce role-based access (interns cannot use GPT-4 for code generation), use-case restrictions (marketing can use AI for copy but not for customer data analysis), time-based controls (no AI access outside business hours for contractors), and approval workflows (legal review required for AI-generated contracts). The Areebi policy builder supports all of these - point solutions support none.

No shadow AI detection

If your DLP tool only monitors one AI endpoint, employees who switch to a different tool bypass it entirely. Shadow AI detection requires visibility across all AI tools - browser-based, API-based, and embedded. Areebi's browser extension detects AI tool usage across 50+ platforms and routes employees to the governed workspace.

No compliance mapping

DLP logs show "sensitive data detected at timestamp X." Compliance requires mapping that detection to a specific control in HIPAA, SOC 2, or the EU AI Act, then producing evidence that the control operated continuously. Point solutions provide raw logs; Areebi provides compliance-ready evidence packages.

No private deployment

Most DLP point solutions operate as SaaS - meaning your prompts route through their infrastructure for scanning. For organisations in regulated industries, this creates a new data-processing relationship that may itself require regulatory review. Areebi deploys privately within your infrastructure, so prompt data never leaves your environment.

Organisations that choose point solutions inevitably discover they need more capabilities. The result is a patchwork of tools that creates its own governance problems.

The typical point-solution stack

Capability	Tool	Annual cost
DLP for AI prompts	Nightfall AI / Protect AI	$15,000–$30,000
AI workspace	Custom build or separate SaaS	$20,000–$50,000
Audit logging	SIEM integration + custom pipelines	$10,000–$25,000
Shadow AI monitoring	CASB add-on or manual tracking	$15,000–$40,000
Compliance reporting	GRC platform or manual process	$20,000–$50,000
Integration engineering	Internal DevOps/SecOps time	$30,000–$75,000
Total		$110,000–$270,000

Areebi: one platform, one price

Capability	Included	Annual cost (100 users)
All of the above + more	Yes	$30,000–$60,000

The cost savings are significant, but the operational savings are even more important. Every integration between point solutions is a potential failure point. When the DLP tool updates its API, does the audit pipeline break? When the workspace adds a new model, does the DLP scanner cover it? These integration maintenance tasks consume engineering cycles indefinitely. See Areebi pricing for transparent, all-inclusive rates.

Beyond direct costs, fragmented tooling creates vendor-management overhead: separate contracts, separate support channels, separate security reviews, separate SOC 2 assessments for each vendor. A single-platform approach from a vendor you can trust collapses this complexity into one relationship.

AI governance is inherently cross-cutting. A single employee interaction - one prompt to one model - can trigger DLP rules, policy checks, audit logging, compliance evidence generation, and shadow AI tracking simultaneously. These are not independent functions; they are interdependent layers of a single governance decision.

Point solutions treat each layer as a separate problem. Areebi treats them as facets of one unified control plane.

Unified data model

Every AI interaction in Areebi flows through a single event pipeline. The DLP engine, policy engine, audit logger, and compliance mapper all process the same event with the same metadata. This eliminates data reconciliation issues and ensures that every control operates on consistent, complete information.

Atomic policy decisions

When a user submits a prompt, Areebi evaluates DLP rules, access policies, use-case restrictions, and compliance requirements in a single pass. The decision to allow, block, redact, or escalate considers all governance dimensions simultaneously. Point solutions make isolated decisions that may conflict - the DLP tool allows a prompt that the policy engine (if one existed) would block.

Single pane of glass

Governance teams need one dashboard, not five. Areebi's admin console shows AI usage, DLP events, policy violations, compliance posture, and shadow AI activity in a single interface. This is not a reporting convenience - it is a governance requirement. Fragmented visibility creates fragmented governance.

For healthcare organisations managing simultaneous HIPAA, state privacy, and clinical AI requirements, the platform approach is not optional. Point solutions cannot coordinate the overlapping compliance obligations that regulated industries face.

Point-solution pricing appears lower because you are buying less. But per-dollar-of-governance-coverage, Areebi delivers 3–5x better value.

Consider the cost per governance capability:

Metric	Point solution	Areebi
Cost per user/month	$15–20 (DLP only)	$25 (full platform)
Capabilities included	1 (DLP)	8+ (DLP, workspace, policy, audit, compliance, shadow AI, SSO, deployment)
Cost per capability/user/month	$15–20	~$3
Additional tools required	4–6	0
Integration engineering	$30K–$75K/year	$0
Time to full governance	3–6 months	2–4 weeks

The framing that point solutions are "cheaper" only holds if you accept that DLP alone constitutes AI governance. No auditor, no regulator, and no CISO makes that argument. Complete governance is not optional - it is a matter of when, not if. Starting with a platform is faster and cheaper than assembling one from parts.

Ready to see how Areebi replaces your point-solution stack? Take the free AI governance assessment to identify your coverage gaps and get a customised migration plan.

Areebi was designed from the ground up as a complete AI governance platform, not a DLP tool with features bolted on. Every capability is integrated, not stitched together.

The AI workspace that drives adoption

Employees get a governed AI workspace that is genuinely better than consumer alternatives. Multi-model access (GPT-4, Claude, Gemini, Llama, Mistral), document-based RAG, conversation history, workspace collaboration, and custom agent creation - all within the governance boundary. Point solutions ask employees to accept worse tooling in exchange for compliance; Areebi makes compliance the path of least resistance.

DLP that actually covers everything

Areebi's DLP engine scans prompts and responses - because sensitive data can appear in model outputs too. Custom detection patterns let you protect organisation-specific sensitive data (internal project names, unreleased product details, M&A targets) that generic DLP classifiers miss.

Policy enforcement beyond data classification

The policy builder enforces rules that DLP tools cannot express: role-based model access, use-case restrictions, approval workflows, output format requirements, and time-based controls. Policies are versioned, auditable, and testable in staging before production deployment.

Compliance out of the box

Pre-built compliance templates for HIPAA, SOC 2, ISO 27001, NIST AI RMF, and the EU AI Act. Continuous monitoring, real-time dashboards, and on-demand audit evidence export. No manual evidence collection. No last-minute audit prep scrambles.

Deployment flexibility that point solutions cannot match

Private cloud, on-premises, or air-gapped deployment. Your data stays in your environment - no routing prompts through a third-party SaaS for DLP scanning. For regulated industries and security-conscious enterprises, this is a non-negotiable requirement that SaaS-only point solutions simply cannot meet.

Request a demo to see the full platform in action and compare it directly against your current point-solution stack.