Monetizing AI / vCon with Usage-Based Billing
As AI technologies go mainstream, the way companies price and bill for these services is rapidly evolving. Whether you're offering large language models, speech-to-text engines, or AI image generators, one thing is clear: billing must keep pace with AI’s dynamic, usage-driven nature.
Industry forecasts predict that usage-based and conversational billing will dominate AI monetization by 2025, with 60% of SaaS providers expected to adopt token-based or hybrid models (Source: Gartner, 2024 AI Trends Report).
The Need for a System Built for Complexity and Ready for AI.
As AI continues to disrupt industries, the winners will be those who can package, price, and bill for AI services quickly and accurately.
What Is AI Billing Software?
✅ Real-Time Usage Capture
Whether you're billing by tokens, API calls, GPU time, or data volume processed, Usage engines need to be able to handle it in near real time. Our platform supports granular, event-level data ingestion, similar to telecom call detail records (CDRs), but tailored for AI workloads.
- Customer-facing reports for usage transparency
✅ vCON File Monetization (Voice + Content + Context)
A new frontier in AI monetization is emerging with vCON files (the IETF Internet Standard for Virtualized Conversations). These standardized JSON containers record not only call metadata but also conversation content, AI-enriched content, and event context.
As communication platforms evolve, these files are becoming the next-generation equivalent of Call Detail Records (CDRs) — but far richer. A single vCON may include:
- Usage Elements: Duration, participants, and media type (voice, video, text)
- AI Enrichments: Transcriptions, sentiment scores, entity tagging, summarization, or compliance labeling
- Metadata: Device IDs, timestamps, channel sources, and enrichment provider details
Because each vCON aggregates multiple layers of chargeable activity, billing systems must treat them as composite records, rating each element individually while maintaining a linkage to the original conversation record.
TimelyBill’s event-based architecture is already well-suited for this model. Each enrichment or analytic process inside a vCON can be billed independently, such as:
- Base communication fee (duration, participants, or media type)
- Per-enrichment fee (e.g., sentiment analysis, translation, transcription)
- Storage or retrieval charges (based on file size or retention duration)
- API access or AI engine processing fees
By treating vCONs as multi-layered usage containers, service providers can introduce per-AI enrichment billing while preserving visibility and auditability across systems, much like how telecom carriers rate composite usage in real-time.
✅ Flexible Biling & Rating
Flexible billing rules allow AI vendors to create custom pricing structures tailored to their unique business models, ensuring accurate monetization of AI services. In the dynamic AI landscape, where usage patterns vary across models (e.g., large language models, speech-to-text, or image generators), industries, and customer segments, the ability to define and adjust billing rules is critical. A robust billing system enables companies to adapt pricing in real time, aligning with diverse AI workloads and customer needs without being constrained by rigid, one-size-fits-all solutions.
- Charge per 1,000 tokens (like OpenAI)
- Bill by the minute for transcription (like Whisper)
- Add surcharges for priority compute or model tiers
Need to roll up usage across departments, resellers, or tenant environments? We do that too.
✅ Workflow Management
AI services increasingly rely on granular, event-based billing triggers (like token usage, compute cycles, or API calls), and the ability to orchestrate billing actions in real-time becomes mission-critical. As AI-driven workloads generate these events, a workflow manager ensures that related actions are triggered automatically.
- Automate event triggers when system events occur, like tracking usage, creating invoices, or detecting unusual activity.
- Rule-based workflows on conditions like token limits, compute overuse, or customer-specific service levels.
- Log all automated tasks with time-stamped logs for compliance, transparency, and accurate billing.
✅ Multi-Tenant & API-First Architecture
A cutting-edge billing solution, designed with an API-driven, cloud-native, and scalable architecture, is crucial for AI vendors seeking to efficiently monetize services and grow without limits. Unlike outdated, on-premises systems that struggle with flexibility, a cloud-based platform harnesses distributed computing to manage the high-volume, variable demands of AI workloads, such as millions of API calls or token-based transactions.
An API-driven design enables seamless integration with AI platforms, while multi-tenant capabilities accommodate diverse customer segments. This architecture streamlines operations, enhances customer satisfaction, and ensures scalability in the fast-paced AI market.
- Onboard customers automatically
- Feed in usage files via secure FTP
- Generate branded invoices or push to external systems
- Resellers and platform partners can white-label AI services
✅ More Than Billing — A Full OSS/BSS Platform
Independent research from respected organizations confirms that integrated billing systems lead to significant cost savings and operational efficiencies. A Deloitte report outlines how modernizing billing infrastructure helps providers reduce overhead, accelerate time-to-market, and improve customer satisfaction by aligning billing with business goals.
In addition, TM Forum's 2020 Digital Transformation Tracker reported that 60% of service providers cite increased agility, such as faster service launches, as a key benefit of integrated OSS/BSS systems.
Gartner estimates that telecom billing errors account for 5–12% of expenses, many of which can be avoided through system integration. TM Forum further suggests that industry-wide billing errors cost providers approximately $50 billion annually—losses that integrated platforms help prevent by providing accurate, real-time billing data.
- Automated invoicing and dunning
- Customer portals and self-service tools
- Taxation integration
- Reporting and audit trails
Use Case #1: AI-as-a-Service
Imagine you're a company offering a GenAI API:
- Text, LLMs: Billed by tokens (a unit of text processed by AI)
- Audio, speech recognition: Billed by the minute
- Images, computer vision: Billed per generation
With an AI billing solution, you can:
- Track all usage per customer, per model
- Apply dynamic pricing (tiered, flat-rate, or hybrid)
- Display usage data in customer portals
- Automate billing at scale across thousands of accounts
Use Case #2: AI-Enhanced Communications (vCON Billing)
Imagine a unified communications provider offering AI-enriched call services. Each customer call generates a vCON file that encapsulates:
- Audio recording and transcription
- Real-time translation
- Sentiment and keyword analysis
- Summary generation for CRM logging
Each enrichment is processed by a different AI engine — and each can be rated, charged, and reported separately:
| Component | Unit | Billing Model |
|---|---|---|
| Base Call | Minutes | Standard telecom rate |
| Transcription | Minutes processed | $0.01/min |
| Translation | Characters translated | $0.0005/char |
| Sentiment Analysis | Conversation | $0.02 per file |
| Summary Generation | API event | $0.05 per call |
| Example rates for illustration purposes; adjust according to contract and provider. | ||
Future-Proof Your Monetization
Look for a billing platform that provides the flexible infrastructure to enable next-generation companies to accurately meter and monetize AI usage, regardless of how it's consumed.
Choosing the right billing automation tool isn't just about convenience—it can have a direct impact on revenue integrity and regulatory compliance. Consider TimelyBill, which has long been trusted by telecom providers to handle real-time rating and complex billing logic.
Whether you're launching a new AI product or scaling up usage-based SaaS, TimelyBill gives you the billing agility you need without compromising control or compliance.
As AI technologies continue to reshape industries, the importance of a billing system that can adapt to diverse and dynamic usage patterns cannot be overstated. Drawing from decades of experience in telecom billing, TimelyBill is uniquely positioned to support AI vendors in implementing flexible, customer billing solutions that meet the demands of today's market.
By leveraging our proven infrastructure, businesses can confidently navigate the complexities of AI monetization, ensuring accuracy, scalability, and compliance at every step.
Learn more about our Workflow Manager and how it automates AI-driven tasks. Or explore our usage-based billing tools for more technical insight.
TL;DR Summary
Usage-based billing is expected to become the dominant model for monetizing AI services by 2025, with 60% of SaaS providers adopting token-based or hybrid models. To succeed, AI vendors need flexible, real-time billing systems that handle complex usage patterns (e.g., tokens, API calls, GPU time). Key features include real-time usage capture, flexible billing rules, automated workflows, multi-tenant API-first architecture, and integrated OSS/BSS platforms. TimelyBill, trusted in telecom, offers a scalable solution for AI monetization, ensuring accuracy, transparency, and compliance.
With standards like vCON blurring the line between communication and computation, forward-thinking billing systems will need to manage both usage and content valuation within a single unified flow. TimelyBill’s heritage in rating complex, event-rich data makes it an ideal foundation for this next wave of AI-driven communications billing.
Disclaimer: This post is intended for informational purposes only. For implementation advice tailored to your organization, consult with a qualified expert in billing or financial systems.