A focused round to take Avokaido from validated demo clients to enterprise general availability — and to prove a pricing model that grows with every line our customers ship.
Full terms, financial model and data room available on request. Standard investor protections and pro-rata rights.
Three forces are converging at once. The team that pairs builder speed with enterprise trust takes the category.
Coding agents collapsed the cost of shipping software. The bottleneck moved from “can we build it?” to “can we trust what gets built?”
59% of enterprises plan to adopt AI development tooling. But IT cannot say yes to tools that leak data, dodge audit, or lock code away.
Every AI builder optimises for speed. None of them hand IT the controls. Avokaido is built governance-first — that is the wedge.
One number, no negotiation: a 10% markup on the AI token spend customers already make. Revenue expands with usage — not with seat counts or renewal arm-wrestling.
The entire pricing model. No seats, no tiers, no platform fee.
Seat-free by design — revenue expands with usage, not headcount negotiations.
Software-only delivery on top of customer-owned infrastructure.
Speed alone is commoditised. Trust is not. Every advantage below is structural — competitors can’t bolt it on later.
Customers keep their Claude, GPT & Gemini relationships and data. We never resell tokens — alignment, not lock-in.
Enterprises set their own security level: tenant isolation, GDPR-ready handling, audit logging. IT configures the guardrails once.
No black box. Every app ships to the customer’s own repos with quality gates — trust that competitors can’t retrofit.
10% on token spend. We grow only when customers ship more. No seats to negotiate, no friction to expansion.
Two founders who’ve felt the problem firsthand — building enterprise-grade software without enterprise-grade headcount.
Leads product and go-to-market. [TODO: 1–2 line background — prior companies, domain expertise, what he’s shipped before.]
LinkedInLeads engineering and platform architecture. [TODO: 1–2 line background — technical credentials, prior systems built.]
LinkedInReach out for the full data room — financial model, terms, and a live product walkthrough.