Every other tool prices per-seat and penalizes you for adding teammates. We charge for knowledge captured and queried — the unit that actually scales with how much value your AI agents deliver. Start with 500 free credits. No card required.
1 credit = 1 KnowledgeUnit ingested · OR · 10 agent retrievals · OR · 1 corpus snapshot.
Annual prepay saves 20%. Overage priced at $0.10/credit. Hard caps available.
How credits work
A credit is what you pay when your corpus changes or when an agent reads from it. Everything else — the web app, the MCP server, the integrations — is included.
gheist_search or gheist_get calls from your AI agents equal 1 credit. Reads are cheap because embeddings are cached.Reason from your team's shape to your monthly credit spend.
Just shipped MVP. Adding 1 ADR/week, 3 PR decision notes/week. Running Claude Code + Cursor. ~20 agent queries/engineer/day.
Mature product, active incident response. ~40 units/week (ADRs + PRs + incidents). Heavy agent usage, ~60 queries/engineer/day.
Multiple services, active on-call rotation. ~400 units/month across the org. Every engineer uses Claude Code + Copilot heavily.
Going over? Overage billed at $0.10/credit at month end. Nothing turns off; you just get an extra line item. Set a hard cap in your billing console if you want certainty.
Why not per-seat?
Cursor, Copilot, Glean, Notion AI, Confluence — every adjacent tool bills per seat. That model penalizes hiring and creates zero expansion pull as your AI agents get more capable. Gheist's credit unit grows with your AI adoption depth, not your headcount.
Frequently asked
Anyone on your team with read access to the Gheist web app. We don't count AI agents, view-only auditors, or external contractors against your teammate cap. If you have 30 full-time teammates and 15 contractors who occasionally collaborate, you're at 30.
Nothing breaks. You move to overage at $0.10/credit, billed at month end with a 14-day grace period. Your agents keep querying, your integrations keep syncing. If you want certainty on your bill, set a hard cap in the billing console — when you hit the cap, capture slows to essential events only until the next period.
Yes, for 60 days. After that they expire. This matches usage-based conventions (AWS, Heroku, Vercel) and prevents stockpiling. If your usage is genuinely bursty, annual commit smooths it out.
Per-seat prices the wrong thing. The value Gheist creates is captured knowledge × agents that can read it — which correlates with your AI adoption depth, not your headcount. Credits map revenue to value. As a side benefit, you can add engineers freely under each tier cap, which removes the usual adoption friction.
Yes, on Enterprise. We ship a Docker-based reference deployment plus Terraform modules for AWS/GCP. Your corpus, embeddings, and agent queries never leave your VPC. You bring your own LLM provider (Anthropic, OpenAI, or a private model). We provide dedicated engineer time during onboarding.
Starter through Business all include a 14-day free trial — full feature access, no credit card. After the trial you can convert, downgrade to Free, or cancel. We email you on days 7, 12, and 13 so you're never surprised.
Prepay 12 months up front, save 20% off list. Payment by card, ACH, or invoice. We'll generate a one-line order form for procurement if needed. You can still upgrade mid-year; we pro-rate the difference and extend your renewal date.
All 5 MCP tools (gheist_search, gheist_get, gheist_record, gheist_ask_human, gheist_log_outcome), the web app, provenance chains, and the full ingestion pipeline. The difference between tiers is credits, integration breadth, SLA, and enterprise features (SSO, audit logs, self-host).
Three triggers usually apply: (1) you need VPC / on-prem / BYO models, (2) you need SSO + SCIM + audit logs for compliance, (3) you're >500 engineers or credit consumption regularly exceeds Growth's 100k/month. Enterprise starts at $100k ACV and is priced on your specific seats + estimated usage.
Start on the Free tier (500 credits, no commitment). After 2-3 weeks you'll have real usage data and can pick a tier with confidence. Almost all teams land between Starter and Team for their first paid month.
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