SaaS Spend Management

Part of the worlds-biggest-software-project initiative.

An AI-native platform that discovers every SaaS subscription in your organisation, reclaims unused licences, and arms you with benchmark data to negotiate better renewals.

SaaS Spend Management gives IT, Finance, and Procurement teams a single system of record for every software subscription -- including shadow IT adopted without approval. It automates discovery across SSO logs, corporate card feeds, and browser telemetry, tracks per-user licence utilisation, manages renewal calendars, and provides benchmark pricing intelligence to support vendor negotiations. The average enterprise runs hundreds of SaaS applications, many overlapping and many underused; this project targets the immediate, measurable cost savings that come from reclaiming dormant licences and renegotiating contracts with data.

Why SaaS Spend Management?

Every incumbent is expensive and opaque. Zylo, Torii, Zluri, and Vertice all require enterprise-negotiated contracts with no publicly listed pricing. There is no credible open-source or affordable option for organisations with fewer than 100 employees.
Discovery is fragmented. Most tools depend heavily on a single signal source (SSO logs or card feeds). Organisations without centralised SSO see significantly reduced coverage, and card-feed-only tools miss free-tier and departmental purchases entirely.
Vendor negotiation intelligence is locked behind managed services. Vertice, Sastrify, and Spendflo bundle human negotiation teams at premium cost. The benchmark data that powers those negotiations could be crowd-sourced and made accessible without a professional-services surcharge.
Spend management and security posture are sold separately. Buyers who need both SaaS cost visibility and shadow IT risk assessment typically purchase two products from two vendors. Combining SSPM and spend management in a single lightweight product is an open gap.
AI tool sprawl is a new, unsolved problem. Tracking token-level spend across ChatGPT, Claude, and other AI services is nascent even in market leaders. Most platforms cannot tell you which team is burning how much on which model.

Key Features

SaaS Discovery and Inventory

Automated discovery via SSO log integration (Okta, Azure AD, Google Workspace)
Expense and corporate card feed ingestion for complementary spend discovery
Browser extension telemetry capturing tools invisible to SSO and card data
Shadow IT flagging against an approved application registry
AI-driven application categorisation and duplicate/overlap detection

Licence Utilisation and Cost Optimisation

Per-user last-login and feature-usage tracking for each application
Dormant licence identification with automated reclamation workflows
Spend analytics by vendor, department, and category
Peer-benchmark pricing data for identifying overpayment
Predictive renewal forecasting with projected spend trajectory

Renewal and Contract Management

Centralised renewal calendar with configurable advance-warning alerts (90/60/30 days)
Contract repository with AI-assisted metadata extraction (auto-renewal clauses, price caps, termination windows)
AI-generated negotiation playbooks per vendor based on benchmark data
Structured procurement intake with budget approval routing and preferred-vendor enforcement

Access Governance and Lifecycle Management

Onboarding and offboarding workflows tied to HRIS data
Access mapping per user per application with excessive-permission flagging
No-code workflow automation for provisioning, deprovisioning, and approval routing
Intelligent offboarding: AI-inferred application list for departing employees based on job role

AI Spend Tracking

Token-level cost tracking by model, user, and team for AI/LLM tools
Duplicate AI subscription detection across the organisation
Shadow AI discovery and security policy enforcement

AI-Native Advantage

AI transforms SaaS spend management from a passive dashboard into an active cost-reduction engine. LLM-powered contract parsing extracts renewal clauses, price escalation caps, and termination windows from uploaded PDFs without manual data entry. Semantic similarity detection identifies overlapping applications that keyword-based matching would miss. Natural-language queries let non-technical stakeholders ask questions like "show contracts renewing in Q2 over $100K" without building reports. Anomalous spend detection uses ML-based alerting to flag unusual licence growth or cost spikes before they appear on the quarterly review.

Tech Stack & Deployment

The platform targets self-hosted and cloud deployment. SaaS discovery relies on standard identity protocols (SCIM, SAML, OAuth 2.0, OpenID Connect) and documented APIs from SSO providers, HRIS systems (Workday, BambooHR), and ITSM tools (Jira Service Management, ServiceNow). A REST API with webhook support enables integration with existing IT toolchains. An MCP server can expose inventory and renewal data to AI coding agents and assistants. All core discovery techniques -- API polling, SSO log parsing, licence utilisation calculation -- use publicly documented protocols with no patent encumbrances.

Market Context

The SaaS management platform market serves enterprises spending millions annually on software subscriptions, with buyers spanning IT, Finance, and Procurement. Zylo's benchmark database covers $75B+ in SaaS invoices; Vertice tracks pricing from 32,000+ vendors. Incumbent pricing is enterprise-negotiated and undisclosed, effectively locking out mid-market and smaller organisations. Spendflo and Vertice claim 20-30% cost reductions through managed negotiation services, suggesting significant savings potential that an open, data-driven alternative could unlock without the professional-services overhead.

Project Status

This project is in the research and specification phase. Contributions, feedback, and domain expertise are welcome.

Contributing

We welcome contributions from developers, domain experts, and potential users. See CONTRIBUTING.md for guidelines.

Important: All contributions must be your own original work or clearly attributed open-source material with a compatible licence. Copyright infringement and licence violations will not be tolerated and will result in immediate removal of the offending contribution. If you are unsure whether a piece of code, text, or other material is safe to contribute, open an issue and ask before submitting.

Licence

Licence to be determined. See discussion for context.