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Zephyr Analytics · GTMOSAccounts / Zephyr Analytics
P8Monitor
Low fit or intent; no action recommended.
46/ 100C
Scores 46/100; strong fit (27.5/35), technical (12.6/15); driven by Technology adoption, Relevant job posting. Weak on intent, timing, engagement.
Account fields with provenance| Field | Value | Source | Confidence |
|---|
| Industry | Martech | demo_webscan | 88% |
| Employees | 761 | crm_import | 87% |
| Headcount growth (12m) | 17% | — | — |
| Segment | Enterprise | — | — |
| HQ | Chicago | demo_webscan | 83% |
/ 15
Martech is an adjacent industry (half credit).
Company size12 / 12761 employees is inside the sweet spot (250–5,000).Geography8 / 8Headquartered in a primary region (NA).Intent
- Relevant job posting1.7 / 6Posted: ML Platform Engineer (LLM Ops), observed 46 days ago. Confidence 85%, strength 0.65 (typical 0.65), 30-day half-life → 29% of 6 pts.
- Technology adoption1.9 / 5Adopted vLLM, observed 89 days ago. Confidence 75%, strength 0.60 (typical 0.60), 90-day half-life → 38% of 5 pts.
Timing
- Headcount growth1.8 / 3Headcount grew 17% in 12 months.
Technical
- AI/ML team3.6 / 6AI/ML org of ~25 engineers: meaningful but still growing.
- LLM stack6 / 6Runs 6 LLM-stack technologies: Anthropic, Hugging Face, LangChain, Pinecone, pgvector, vLLM.
- Platform maturity3 / 3Production platform maturity: Datadog, Kubernetes, Vertex AI.
Engagement
- Sales engagement0 / 5No two-way sales engagement in the last 90 days.
| Funding stage | Series C | demo_webscan | 75% |
| AI/ML team | 25 | demo_hiring | 84% |
| Tech stack | AnthropicDatadogHubSpotHugging FaceKubernetesLangChainPineconePostgreSQLRedisVertex AIpgvectorvLLM | 70% |
Last enriched 24d ago · record source demo_seed:list_import
Job PostingPosted: ML Platform Engineer (LLM Ops)Sep 2, 2026
Job posting 'ML Platform Engineer (LLM Ops)' mentions evaluation and reliability of LLM systems (DEMO).
demo_signal_feed · confidence 85% · strength 0.65 · demo
Tech AdoptionAdopted vLLMJul 21, 2026
Technographic scan detected vLLM in Zephyr Analytics's stack (DEMO).
demo_signal_feed · confidence 75% · strength 0.60 · demo