Get Synvolv into the live request path
without rebuilding your app first.
Synvolv is designed to drop into the request flow teams already have. Your app sends an AI request with tenant, feature, and model context. Synvolv evaluates budget, tenant policy, and routing conditions before provider execution — through an OpenAI-compatible endpoint.
Fast integration matters because runtime control only wins if
teams can adopt it before cost pain gets worse.
The Request Pipeline
App sends request with X-Tenant-ID headers
Synvolv evaluates Policy Boundary (Budget, Model, Reroute)
If valid, request is forwarded to Provider (LLM)
Outcome is captured in the Audit Loop
Synvolv Engine
Quickstart here means:
send traffic, pass context, turn on your first control.
The goal of this page is not to document every endpoint. It is to help teams do the first real thing: send an AI request through Synvolv, include the tenant and feature context Synvolv needs, and see a budget, routing, or attribution control start working in the live request path.
That is already the core product story in your materials. Start with one request path. Then add attribution, budgets, and policy depth.
First request. First context. First control.
The first three
things to do
Start with the minimum path that proves the product is in control: route one request through Synvolv, send the context that matters, and verify that Synvolv can evaluate or enforce something before provider execution.
Step 01Point your app at Synvolv
Use the OpenAI-compatible entry point so your requests flow through Synvolv instead of going directly to the provider. The deck explicitly frames this as drop-in with an OpenAI-compatible endpoint.
Step 02Send the context Synvolv needs
Include tenant, feature, and model context so Synvolv can apply budget checks, tenant policy, and routing policy correctly. Your materials repeatedly position spend and control around tenant, feature, and model.
Step 03Turn on one visible control
Start with something observable: tenant attribution, a budget boundary, or a routing rule you can test. Synvolv's own product surfaces are built around budgets, tenant control, and routing tests.
Good first proof
See spend by tenant, feature, and model.
Good first policy
Set a budget or routing rule and confirm Synvolv evaluates it in path.
Good first outcome
A request no longer goes straight to the provider without logic in between.
"A useful quickstart is not 'hello world.' It is the first moment you cansee Synvolv controlling something realin the request path."
See example request flowQuickstart proves the request path.
The next docs should deepen control.
Once traffic is flowing through Synvolv and one control is working, the next docs follow the same product logic: first attribution, then budgets, then routing and autopilot.
Synvolv becomes more valuable as more live traffic, tenant controls, and policy depth move through the platform. This progression ensures business systems depend on trustworthy technical control.
Headers and context
Explain how tenant, feature, and model context should be passed consistently so attribution and policy can work correctly.
Budgets and enforcement
Show how project and tenant boundaries should be defined so policies hold before spend runs away.
Routing and autopilot
Document how teams define routing policy, test outcomes, and trigger downgrade, cap, cache, or pause under pressure.
Exports and governance
Document the finance and governance layer as Synvolv expands into audit trail, exports, and stronger tenant governance.
"The docs should deepen in the same order the product becomes operationally valuable:context → attribution → budgets → policy → governance."
See who should lead rollout firstThe rollout usually starts with the team
closest to the request path and expands from there.
The platform or engineering lead is usually the first person pulled in when usage spikes or routing breaks margin. That makes them the natural first technical owner.
But the product is not only for engineers. The real question becomes commercial viability as usage grows. Rollout begins with technical control and expands into finance and business policy.
Step 1 — Platform or engineering lead
Get traffic through Synvolv, pass context, and prove one real control in the request path.
Step 2 — Product and finance visibility
Use spend by tenant, feature, and model to make attribution useful beyond engineering.
Step 3 — Deeper governance and dependency
Expand into more traffic, more tenant controls, stronger policy enforcement, and finance workflows.
First technical owner
Platform or Engineering Lead
Budget owner
Product Leader, GM, or FinOps Owner
"A good rollout path starts withtechnical control in the request pathand expands into the business systems that depend on that control being trustworthy."
See the product controls this rollout unlocksStart with one request path.
Then prove one control. Then deepen from there.
The best quickstart is not a toy integration. It is the first moment Synvolv starts governing something real in the live request path: attribution, a budget boundary, or a routing rule.
More live traffic, more tenant controls, deeper policy enforcement, finance workflows, and governance depth follow as Synvolv becomes part of the product margin loop.
Built around tenant, feature, and model context, plus in-path evaluation before provider execution
Best fit for multi-tenant AI products with external users, variable usage, and model-driven cost
The best docs entry point is the one that gets a real policy, budget, or attribution decision working in live traffic.