Top solutions for agentic monetization in B2B SaaS

The rise of AI agents in B2B SaaS is reshaping not just how products function, but how they generate revenue. 

As traditional SaaS pricing models struggle to capture the value of AI agents, AI agent pricing models have emerged to create pricing strategies that align with the autonomous and outcome-driven nature of AI agents.

But as more and more agentic platforms are entering the market, the need for platforms that support AI agent monetization is greater than ever. 

In this post, we break down the top platforms purpose-built to handle the complexity of AI-era pricing: real-time usage tracking, outcome-based pricing, and flexible models that grow with your product.

If you’re serious about scaling an AI-powered SaaS business, we’re about to introduce you to solutions for agentic monetization you can’t ignore.

What is agentic monetization?

Agentic monetization, similar to AI monetization, refers to the process of converting agentic capabilities into revenue-generating offerings. It’s the process of generating revenue from artificial intelligence capabilities, features, or products.

Agentic monetization uses AI agent pricing models that are designed to capture the value created by autonomous agents. These are typically AI-powered or agentic systems that act independently to perform tasks, make decisions, or drive business outcomes without constant human input.

Unlike traditional SaaS monetization, which charges for access to features (like a seat-based subscription), agentic monetization charges for the actions, outcomes, or usage of these agents.

This aligns pricing with the actual work agents do, not just who is using the software.

In short, monetizing agentic AI is about aligning price with the value each AI-driven action delivers.

Let's diver deeper into agentic pricing models.

Agentic pricing models

Monetizing autonomous agents requires a new pricing playbook—one that reflects the value of actions and outcomes, not just user access.

Here are the core pricing models powering agentic monetization in modern B2B SaaS:

1. Usage-based pricing

Charge based on the volume of actions an agent performs. This could be per API call, per message sent, per token processed, or any other measurable unit of agent activity.

• Example: $0.002 per AI-generated email or $0.01 per API request.
• Best for: High-volume, transactional AI functions like content generation, data extraction, or communication.

2. Outcome-based pricing

Charge when an agent delivers a specific result—something measurable and valuable to the customer.

• Example: $50 per qualified sales meeting booked by an AI SDR; $0.99 per resolved customer support ticket.
• Best for: Agents driving measurable business outcomes like lead conversion, issue resolution, or revenue generation.

3. Per-agent pricing

Treat each deployed agent as a “digital employee” and assign a recurring price to it, usually monthly.

• Example: $1,500/month per AI customer service agent or sales bot.
• Best for: SaaS products offering agent-as-a-service models where each AI agent operates independently at scale.

4. Hybrid pricing models

Combine base subscriptions with usage or outcome-based fees to balance predictability with performance-based scaling.

• Example: $199/month base + $0.01 per AI action over 10,000 actions.
• Best for: Teams wanting consistent recurring revenue with room to monetize high-usage customers proportionally.

5. Prepaid or credit-based models

Let users buy credits upfront to spend on agent activity, offering flexibility while locking in revenue.

• Example: $500 for 100,000 credits, where each credit = 1 AI action.
• Best for: Self-serve SaaS models or products with unpredictable usage patterns.

5 factors to consider when evaluating agentic monetization solutions

When choosing a platform to implement agentic monetization, consider the following criteria:

1. Scalability and real-time processing: The solution should handle high volumes of events (API calls, transactions) and meter usage instantly.
   
   AI workloads can spike unpredictably, so real-time usage tracking and billing are essential. Ensure the platform can scale with your growth without latency or data loss.
2. Pricing flexibility: Look for support of various pricing models, including subscriptions, usage tiers, per-agent fees, outcome-based charges, one-time add-ons, and so on.
   
   An ideal tool lets you configure or experiment with new pricing plans without custom engineering. This flexibility is crucial as AI pricing models continue to evolve rapidly.
3. Automation and integration: Monetizing AI at scale requires automating the quote-to-cash process end to end.
   
   The platform should integrate with your CRM, payment gateways, and accounting software to sync customer data and invoices. Automation (from capturing usage to invoicing to revenue recognition) reduces errors and manual effort, which is vital for lean teams.
4. No-code vs. control: Consider your team’s technical resources. Some monetization solutions are no-code or low-code, enabling business users to set up pricing and billing logic via dashboards. Others are developer-first, offering granular control through APIs but requiring engineering effort to implement and maintain.
   
   Companies with limited engineering bandwidth may prefer a more out-of-the-box platform like Alguna, while those with complex custom needs might opt for a developer-centric tool.
5. Cost structure: Evaluate how the solution charges you (the vendor). Pricing models for these platforms vary as some charge a percentage of your revenue, some have flat monthly fees, and others are enterprise licenses.
   
   For example, Stripe Billing takes 0.7% of billed revenue with no base fee which is attractive for a startup but can add up at scale. In contrast, an enterprise system like Zuora requires a significant annual subscription (often $50k+ per year) but may offer more robust capabilities. Meanwhile, you have options like Alguna that offer end-to-end agentic monetization solutions for a flat fee, starting at $399. Align the choice with your budget and revenue projections.

By weighing these factors, B2B SaaS companies can find a monetization solution that fits their stage and strategy, whether it’s a lightweight tool for a new AI product or a comprehensive revenue platform for a scaling enterprise.

Comparing top agentic monetization solutions in B2B SaaS

Below is an overview of leading platforms that help SaaS companies monetize AI and usage-based offerings.

We compare who each is best for, key strengths, limitations, and pricing at a glance.

Alguna: The top agentic monetization solution for B2B SaaS

Alguna is an end-to-end AI monetization platform purpose-built for AI-native companies and B2B SaaS. It unifies every part of the monetization process, from pricing configuration and quotes to metered billing, invoicing, and revenue recognition—all in a single source of truth.

Backed by Y Combinator and built by veterans from fintech companies, Alguna focuses on the needs of AI-era SaaS products, supporting monetization models that traditional billing systems weren’t built to handle (like credit-based pricing, per-token, or per-action pricing).

When it comes to monetizing AI agents in a fast-moving B2B SaaS environment, Alguna stands out as the most complete and purpose-built solution on the market. Designed specifically for the complexities of agentic monetization, Alguna offers everything SaaS teams need to turn AI activity into revenue—with no patchwork of tools or custom engineering required.

Built for the AI era

While legacy billing platforms struggle to adapt to usage-based and outcome-driven models, Alguna was designed from the ground up for agentic pricing. It supports everything from per-action billing (like per API call or per token processed) to hybrid plans and per-agent pricing, all configurable through an intuitive, no-code interface. That means your team can launch, iterate, and scale pricing models without touching code or waiting on developers.

End-to-end revenue automation

What makes Alguna unique is its fully integrated quote-to-cash platform. It handles:

• SaaS pricing and packaging
• Real-time usage metering
• No-code CPQ (configure, price, quote)
• Automated billing and invoicing
• Revenue recognition and reporting

This all-in-one approach eliminates the need for separate tools and manual workarounds. Finance, sales, and product teams can stay aligned and move faster.

Scales with you (without taking a revenue cut)

Unlike some monetization platforms that charge a percentage of your revenue, Alguna offers flat-rate pricing that scales predictably. Paid plans start at $399/month, with a free tier available for early-stage startups. This makes it attractive for both emerging AI companies and larger teams managing high-volume usage across enterprise clients.

Why it’s the leader

Alguna isn’t just another billing tool, it’s a complete revenue engine for AI-powered SaaS. It combines the flexibility of a modern metering system with the automation and compliance features of a mature finance stack.

For teams serious about monetizing AI agents effectively and avoiding the technical debt of building billing infrastructure in-house, Alguna is the most complete and scalable solution available today.

Key capabilities of Alguna include:

• Real-time usage metering: Instantly captures usage events via API or connectors and bills customers based on defined metrics (e.g. API calls, tokens, computations) without delay. This ensures accurate billing even for high-volume, granular AI usage.
• No-code CPQ and billing automation: Alguna provides a visual CPQ interface to create custom quotes, add discounts or one-off fees, and turn signed quotes directly into active subscriptions and invoices automatically. Sales and finance teams can go from proposal to cash collection with zero manual data entry.
• Built-in revenue recognition and compliance: The platform automatically handles accounting tasks like deferred revenue schedules and compliant revenue recognition (ASC 606/IFRS 15), producing audit-ready reports. This is critical for SaaS companies that need to recognize subscription and usage revenue properly without spreadsheets.
• Integrations: Alguna integrates with popular CRMs (Salesforce, HubSpot) and accounting tools (QuickBooks, Xero, NetSuite) to sync customer, contract, and payment data. It also offers webhooks and APIs for custom workflows, so Alguna becomes the central hub for all billing and revenue data across an organization.
• Flexible pricing model support: Teams can configure everything from simple subscriptions to complex tiered usage plans, prepaid credit systems, or outcome-based charges – all without writing code. This flexibility means businesses can experiment with pricing (e.g. adding a new AI feature add-on or usage fee) and deploy it live in minutes, rather than waiting on development cycles.

In practice, Alguna enables B2B SaaS companies to iterate and scale their agentic monetization with agility. For example, revenue teams can adjust prices or launch new usage-based offerings in minutes without engineering support.

All quotes, contracts, and invoices flow through one unified platform, eliminating the errors and delays that come from stitching together separate CPQ, billing, and finance tools.

Choosing the right agentic monetization solution

Monetizing AI and usage-based products in B2B SaaS requires a shift in mindset as we’ve gone from selling software access to selling outcomes and usage. 

Today, agentic monetization isn’t optional, it’s foundational for any B2B SaaS company building in the AI era. The right monetization platform doesn’t just streamline billing, but rather, it unlocks scalability, aligns pricing with value, and gives your team the agility to iterate on pricing models without breaking your systems.

Platforms like Alguna lead the way by offering real-time metering, outcome-based pricing, and end-to-end automation built for the speed of modern SaaS.

Whether you're launching your first AI agent or scaling a mature product line, investing in the right agentic monetization solution now means you won't be left behind as the market shifts.

The AI future is already here. Make sure your monetization engine is ready for it.