Spendline - 2026 Pricing, Features, Reviews & Alternatives

Spendline is an in-path AI spend governance proxy for engineering teams running LLM workloads in production. Integration is a base URL change: point your existing OpenAI or Anthropic client at Spendline's endpoint, add three headers, and keep your own provider keys. There is no SDK to install and no application rewrite.

Ten providers are reachable through one endpoint: OpenAI, Anthropic, Google Gemini, xAI, Mistral, DeepSeek, Alibaba Qwen, Together AI, Fireworks AI and Groq, with optional cross-provider rerouting to a cheaper equivalent model under rules you define.

Every request is priced the moment it happens and written to an append-only ledger, attributed to the customer, agent, workflow, feature, team and cost centre that caused it. Budgets are hierarchical across organisation, team, agent and customer, and they are evaluated before the request is forwarded: a call that would breach a cap is refused with HTTP 402 and never reaches the provider. Policy controls cover model blocks and token caps, with alerts for runaway agents and accelerating spend.

For finance, the same ledger produces margin after AI cost per customer and a month-close workflow that reconciles calculated cost against the provider invoice, with corrections recorded as new adjustment rows rather than edits to the original record.

Security and architecture: provider keys are encrypted at rest, every account is tenant-isolated, and all budget and close activity is written to an append-only audit log. Dashboard updates stream in real time over Server-Sent Events.

Spendline is not an observability or tracing tool. It sits alongside Langfuse, LangSmith or Helicone, and acts in the request path rather than reporting after the fact.