Use cases
Six scenarios that each, individually, justify the £499/mo Enterprise tier. Most teams hit at least three of them within the first 90 days of using us.
Cross-provider continuity for distributed teams
For: AI ops leads at multi-provider orgs
Scenario: Alice spent 3 hours in Claude refining the Q3 forecast. Bob needs to continue tomorrow but his license is for ChatGPT. Without us: 30+ minutes of re-briefing. With us: Bob clicks restore_chat, ChatGPT opens with Alice's full context, work continues in 90 seconds.
Outcome: Cross-provider handoff time drops from 30 min to 90 sec. Compounds across every employee × every provider switch × every week.
Employee handover without losing AI institutional knowledge
For: Heads of People + Engineering at growing orgs
Scenario: Sarah resigns after 4 months building the customer-onboarding playbook inside Claude. Without us: she frantically writes Confluence docs in her notice period; Tom rebuilds 60% from scratch anyway. With us: agent transfers cryptographically; Tom inherits 4 months of receipts + memory snapshots on day 1.
Outcome: Employee turnover stops resetting AI institutional knowledge to zero. Reduces onboarding ramp by an estimated 4-8 weeks per role.
Org-wide AI de-duplication
For: CTOs + ops leads at 50-500 person teams
Scenario: Maria opens Claude Monday: "draft a SOC 2 audit prep document." Our org_context_lookup MCP middleware queries the org's receipts and surfaces: "Carlos finished this on May 3rd — see receipts rcpt_01XK... Want to start from his work?" Maria saves a day.
Outcome: Eliminate 15-25% of AI work that's currently duplicated across teammates who can't see each other's past conversations.
SOC 2 + ISO 42001 + EU AI Act audit trail
For: CISOs + compliance leads in regulated industries
Scenario: EU AI Act enforcement starts August 2nd. SOC 2 audit teams now ask specifically about AI-assisted work. Most companies' answer: "we don't have an audit trail." Ours: every AI conversation across every provider becomes a cryptographically signed receipt with model attribution, cost, environment, and per-employee author tag. Evidence packs auto-generate quarterly.
Outcome: Compliance posture upgraded from "we don't know" to "here's the signed evidence pack" with no behaviour change for engineers.
Cost attribution across multiple LLM providers
For: CFOs + FinOps leads
Scenario: AI spend shows up as one terrifying line on the Anthropic + OpenAI invoices. With us: every receipt logs runtime cost in £, tagged with project + team + provider. Break it down by deliverable, by employee, by environment.
Outcome: Turn AI spend from one black-box number into a per-team, per-project, per-deliverable cost ledger that maps to your existing budget categories.
Vendor-lock-in insurance for AI strategy
For: CTOs evaluating multi-year AI vendor contracts
Scenario: IT considers switching from Claude to ChatGPT next year (or adding Gemini for one team). Without us: institutional AI memory built inside the current provider is lost. With us: every conversation is portable JSON owned by your org; switching providers is zero-rebuild.
Outcome: Eliminates vendor lock-in as a procurement risk. Negotiating power against Anthropic / OpenAI / Google increases at every renewal.
Don't see your use case?
Most enterprise AI pain ladders up to one of: continuity, attribution, or audit. Tell us yours.
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