You don't have an API creation problem. You have an API change-management problem. KizunAPI continuously discovers your APIs, maps who really depends on them, and autonomously fixes, tests, and ships every breaking change — before it reaches production.
Live inventory, ownership, and real field-level usage.
Field → service → customer, from production traffic.
Detect → fix → test → deploy → verify, autonomously.
PII detection, anomaly alerts, audit evidence.
Docs, SDKs & portal always in sync with the contract.
MCP tools, agent-to-agent calls, and LLM-backed endpoints are just more contracts that break. KizunAPI treats them as first-class nodes in the same knowledge graph - so an agent tool-schema change gets the same detect-fix-verify loop as a payments API.
Explore the AutopilotFour layers that turn a patchwork of gateways, specs, and tribal knowledge into one self-managing system. We don't replace Apigee, Kong, or AWS Gateway — we make them inputs.
Docs, SDKs, developer portal, and an AI assistant — regenerated automatically whenever the live contract changes.
Inventory, real production usage, dependency graph, ownership, risk, and context. The system of record for API dependencies that doesn't exist today.
Detect → analyze → generate → patch → test → deploy → verify. The autonomous remediation engine — and the heart of the MVP.
Connects to gateways, Kubernetes, Git, CI/CD, cloud, and service mesh. SaaS control plane; self-managed execution.
Knowledge graph + actual production usage down to the field + an automated remediation engine. Nobody has all three.
REST, gRPC, GraphQL, event and data contracts, MCP, and AI agents — all represented as contracts in the same graph.
Every API, endpoint, schema, field, consumer, repo, service, deployment, customer and business capability — connected in one live graph, enriched with real production usage. This is the moat: it's what lets KizunAPI answer "who actually breaks?" in seconds, and it's what the Autopilot acts on. Hover the chain, click any node.
Unlike a static catalog, the Estate Graph is fused with field-level production usage — so it knows the 3 consumers that actually read customer_ref, not the 6 that merely call the endpoint. That precision is what turns a breaking change from a day-long incident into an 11-minute autonomous run.
A third-party payments API ships a breaking v3 at 09:14 UTC. No engineer was told. Step through exactly what KizunAPI does — from detection to a verified, deployed fix.
The control plane runs as SaaS — the intelligence, the graph, the migration engine. The execution and telemetry stay inside your environment. This hybrid split matches how enterprise security teams already buy.
API intelligence, dependency graph, change detection, impact analysis, migration engine, policy, and AI agents.
Gateways, services, traffic, telemetry, runtime enforcement, and local execution — nothing sensitive leaves your boundary.
SSO, RBAC, VPC isolation, full audit trail, and data retention controls — the way security teams expect to consume it.
Illustrative voices representing the personas and pain points surfaced in customer discovery across fintech, SaaS, and regulated enterprise.
"We genuinely don't know how many external APIs we depend on. We find out when something breaks."
"The last breaking change pulled nine engineers off roadmap for a full day. Nobody could tell me the blast radius."
"If software could detect, patch, test and deploy an API change for us, it would eliminate most of what my team does on migrations."
KizunAPI ingests from the gateways and tools you run today and makes them inputs into the knowledge graph. No rip-and-replace on day one.
Import existing API configs and specs; we start building the dependency graph from your gateway inventory immediately.
See how →Connect repos and pipelines so we can map call-sites and open migration PRs where the code actually lives.
See how →Replace the manual oasdiff "keep-a-baseline-and-re-run" hack with continuous, semantic contract monitoring.
See how →Gateways route traffic, design tools shape specs, observability watches runtime. KizunAPI's wedge is the layer above all of them — a cross-vendor estate graph with ownership, dependency and lifecycle intelligence that no single incumbent delivers end-to-end.
| Capability | KizunAPI | Kong | Apigee | MuleSoft | Postman | Datadog | ServiceNow |
|---|---|---|---|---|---|---|---|
| Live API inventory & ownership | ✓ | ✓ | ✓ | ✓ | ✓ | ✕ | ✓ |
| Design-time governance & linting | ✓ | ✓ | ✓ | ✓ | ✓ | ✕ | ◐ |
| API Catalog | ✓ | ✓ | ✓ | ✓ | ✓ | ✕ | ✓ |
| Cross-platform discovery | ✓ | ◐ | ◐ | ✓ | ◐ | ◐ | ✓ |
| API Estate Graph | ✓ | ✕ | ◐ | ◐ | ✕ | ◐ | ✕ |
| Ownership intelligence | ✓ | ◐ | ◐ | ◐ | ✓ | ✕ | ✓ |
| Dependency / impact analysis | ✓ | ◐ | ◐ | ✓ | ◐ | ✓ | ◐ |
| Lifecycle intelligence | ✓ | ✓ | ✓ | ✓ | ✓ | ✕ | ◐ |
| Cross-vendor control plane | ✓ | ✕ | ✕ | ✕ | ✕ | ✓ | ✓ |
Read it by column, not by row. The incumbents each win their home turf — Kong and Apigee on the gateway, Postman on design and test, Datadog on observability, ServiceNow on cross-vendor workflow. KizunAPI's wedge is the band in the middle — cross-platform discovery, the estate graph, ownership, dependency and lifecycle intelligence — the only column that's a clean ✓ the whole way down. Capability snapshot as of October 2026; vendor features move quickly, so we keep this matrix sourced and dated.
One continuous loop — from discovery to retirement, with as little human intervention as possible.