A runtime control layer that stops bad AI economics before they happen.
Not after a rollback. Not after a finance escalation.
Requests from tenant sources route through Synvolv's unified control plane, dynamically resolving the best AI provider destination while enforcing budget and access policies.
Six surfaces. One in-path pass, evaluated in under eight milliseconds — for every request, every tenant.
Spend caps that fail closed.
Hard ceilings, enforced before the spend commits — scoped to tenant, feature, and route. The first gate any request meets, and the most opinionated. Nothing reaches a model unless the budget says yes.
Proactive unit economics that trigger before the spend is committed. Not after reconciliation. Not in a dashboard.
live·sample feedControls execute while the request is still live. Anything else is observability.
Teams act before overspend becomes a rollback or a finance escalation.
OpenAI-compatible endpoint. Standard headers. No SDK lock-in.
From the moment a request enters until it's reconciled — every decision, every dollar, every tenant, in one console.
Batch jobs are 42% of spend on a model you don't need for the task.
38% of queries are near-duplicates. Caching cuts p50 latency and cost.
100% OpenAI dependency caused 12m of downtime this month.
Synvolv fits best when AI usage is live, variable, and tied to customer behavior — production traffic where one request can change the margin.
Attribute and enforce AI spend per customer. Margins stay predictable when one tenant spikes.
Stop runaway chat costs with real-time budget enforcement and automatic model downgrades.
Cap agent loop costs automatically. Halt expensive runaway processes before they consume the budget.
Route across providers, enforce policies, and manage usage across workspaces from one in-path hub.
Turn vague provider bills into precise, auditable unit economics finance and product can defend.
When the gap between sonnet and haiku is the gap between profit and loss on every request.
not the fitLow-volume prototypes, internal experiments, or teams whose only problem is model abstraction.
See every use caseVerified reliability for the live request path. Built to sit in your traffic, not next to it.
Drop-in replacement for any OpenAI-compatible client. Zero code changes to start enforcing policy.
Native support for Anthropic, OpenAI, Gemini, Bedrock, and custom endpoints through one gateway.
Optimized for the streaming-first nature of modern LLMs. Real-time reconcile without added latency.
Every request, decision, and policy action signed, logged, and queryable in real time.
Sub-1ms ingress added to your request path. Built for high-volume, variable traffic shapes.
Per-customer budgets, routing, and attribution out of the box — designed for B2B SaaS architecture.
We'll map your request flow and show where Synvolv triggers outcome changes before unit economics break.
