AI compute commitments are escaping reported capex

[withheld] — Unified AI cost telemetry across GPUs, LLMs, tokens, agents and workloads for cloud, on-prem and hybrid environments — real-time usage, allocation, forecasts, anomaly flags, chargebacks and margin/cost-to-serve attribution. Low-tens of enterprise customers; multi-million daily cost-telemetry events across GPU + LLM stacks. Use cases: AI FinOps benchmarking, cross-vendor LLM cost analytics, GPU utilization modeling, enterprise chargeback, margin/unit-economics analysis, anomaly detection training data, TBM for AI

[withheld] — Multi-team enterprise LLM cost telemetry — per-API-call attribution across OpenAI, Anthropic, Google, AWS Bedrock and self-hosted models, with team/feature/customer/tenant tags, hierarchical budget events, anomaly-flagged spend patterns, monthly executive P&L roll-ups. Founder-stage; low-hundreds of free-tier signups; hundreds of thousands of LLM cost events per month across the free-tier + pilot cohort. Use cases: LLM cost benchmarking across enterprise SaaS features, anomaly-detection training data (retry loops, spikes), unit-economics/usage-based pricing modeling, chargeba…

[withheld] — Enterprise LLM token telemetry — per-request metering, session-level cost attribution (user/team/project/cost-center), budget enforcement events, provider mix and BYO-key usage across OpenAI/Anthropic/Google LLM calls in customer VPCs. Pre-seed/seed-stage; free tier plus small paid pilot cohort; low-thousands of daily LLM-metering events per active customer. Use cases: LLM cost benchmarking, enterprise [withheld] budget modeling, provider-mix analytics (OpenAI vs Anthropic vs Google usage share), prompt-injection labeled training data, PII-scrub classifier training, chargeback modeling

[withheld] — Consolidated enterprise AI-economics telemetry — vendor invoices from OpenAI/Anthropic, SaaS AI add-ons, shadow-AI expense reports, cloud AI usage exports, and GL entries mapped to TBM Solution/Service/Application taxonomy with token-burn, retry-storm and price-change anomaly labels. Mid-stage regional TBM/FinOps vendor (NZ-based, 30 employees, Venture-funded); tens of enterprise customers with millions of monthly TBM-tagged records. Use cases: AI vendor-invoice reconciliation training data, shadow-AI detection classifier training, TBM benchmarking across enterprise IT portfolios, pr…

[withheld] — Multi-provider GenAI token telemetry — input/output/cached tokens per request across OpenAI, Anthropic, Google Gemini, AWS Bedrock, Azure OpenAI, Cohere, Mistral, Databricks and Snowflake Cortex, tied to API key/user/team/product with anomaly-flagged runaway prompts, in one unified schema. Enterprise-scale multi-cloud FinOps vendor; 640 employees; $86.8M revenue; low-thousands of customer accounts; hundred-millions of monthly LLM token events. Use cases: Cross-provider LLM cost benchmarking at enterprise scale, runaway-prompt labeled training data f…

[withheld] — Multi-provider AI spend telemetry: read-only pulls from OpenAI, Anthropic/Claude, Cursor, Hugging Face, Grok/xAI billing APIs feed a per-customer daily spend + anomaly-event stream. Byproduct is normalized cross-vendor token/cost time-series with baselines, forecasts, and severity-tagged anomaly labels — a cleaned alt-data feed on enterprise AI consumption patterns.. Pre-scale seed-stage — <10 employees on Apollo, 77 LinkedIn followers; multi-provider integration breadth is strong but customer base still small.. Use cases: AI-spend alt-data feed for equity analysts tracking enter…

[withheld] — Reconciliation-ready LLM + multi-cloud cost telemetry — per-model-call and per-query records across BYO OpenAI/Anthropic/Gemini/Vertex/Bedrock keys, tied to teams/apps/agents/agent sessions/tools/sources; joined with AWS/GCP/Azure cost + K8s namespace/workload/pod costs; PR-level deploy-to-cost correlation events. Founder-stage; hundreds of dev-tier signups; one named enterprise customer (Adster); hundreds of thousands of LLM + query events per month. Use cases: Deploy-to-cost correlation training data (PR → cost impact), agent runaway-loop labeled dataset for anomaly detectors, mu…

[withheld] — Multi-provider LLM spend telemetry — per-request cost/tokens/latency across OpenAI, Anthropic, Gemini, Bedrock, Deepgram, Eleven[withheld], Together AI, Fireworks, OpenRouter, Cursor and more; with prompt-version A/B analytics, invoice reconciliation (tracked vs billed drift), and customer/feature/team attribution. YC-backed early stage; low-hundreds of paying customers; tens of millions of LLM telemetry events per month. Use cases: Cross-provider LLM cost benchmarking, prompt-version optimization corpora, invoice-reconciliation model training, spike-anomaly detectio…