Pipeline console
A single workspace to tune cache thresholds, RAG depth, compression level, and PII policies — aligned with what the API actually runs.
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TokenSaverGovern LLMs · Cut cost · Secure at scale
LLM governance to cut cost, optimize usage, and secure every model call at scale
TokenSaver is the control plane for all your LLM traffic: enforce policies, access, and budgets; shrink token bills with semantic cache, RAG, and compression; and keep data safe with PII controls — in one predictable pipeline with full observability. Swap models without rewiring safety or retrieval.
Request a demo to see governed LLM at work · One proxy · Cost-aware modules · Policies & spend controls · Works with OpenAI, Anthropic, Google, and more
Early Adopter Program: join teams already scaling on TokenSaver and help shape upcoming enterprise capabilities.
Provider-agnostic — use the models you already trust
Same governance, optimization, and security layer in front of OpenAI, Anthropic, Mistral, Google Gemini, and more — route and compare models without duplicating policies or losing cost visibility.
Built for the move from pilot to production: one control plane as usage, providers, and internal stakeholders grow.
OpenAI
Anthropic
Mistral AI
Google Gemini
Platform
What's powering TokenSaver
Four capabilities that work together — not a pile of disconnected APIs. Configure once, override per request when you need to.
Product teams get business value fast; platform and security teams keep governance, spend control, and reliability as adoption scales.
AI observability (OpenTelemetry)
Instrument LLM traffic with OpenTelemetry-friendly traces and metrics across every pipeline step. Expose the same signals to Prometheus and Grafana for alerting, SLOs, and cost or latency dashboards your platform team already runs.
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RAG & knowledge
Ingest PDFs and retrieve grounded chunks with multimodal-ready storage — context that stays scoped to the right user and workspace.
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Trust by design
Data sensitivity by design: automatic PII detection and configurable anonymization or redaction on every exchange, so regulated or personal content is stripped before it reaches model APIs. Harden data flows against accidental leakage to LLMs and downstream logs while you scale usage with confidence.
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Intelligent routing
One governed path from prompt to model response
Every call flows through the same modules — so you optimize tokens, enforce guardrails, and keep audits simple. Swap providers without losing cost signals or safety posture.
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Lifecycle tools
Tools to manage the full request lifecycle
Test overrides, inspect per-step metrics, and correlate runs with traces — low-friction operations for platform teams and app owners alike.
See use casesArchitecture
Trusted pipeline architecture
Embed anywhere your apps run — supervise usage centrally, enforce org boundaries, and keep provider keys off client devices.
Use cases
TokenSaver powers critical LLM workflows
Same pipeline, different jobs — customer-facing or internal.
Customer support
Grounded answers with RAG, redacted transcripts with PII policies, and cache for repeat intents.
Benefit: Lower cost per ticket, faster replies.
Internal copilots
Central keys, workspace isolation, and spend visibility across teams — without shadow IT keys.
Benefit: Governance without blocking builders.
Research & docs
Long-context compression before the model call, retrieval over your knowledge base, full run history.
Benefit: Deeper context, controlled spend.
Analytics & data apps
Trace IDs, token and cost breakdowns, export-friendly metrics for FinOps and security reviews.
Benefit: One source of truth for LLM spend.
Trust
Trusted operations, built in
Guardrails and visibility that stay aligned as you scale traffic.
Pipeline guardrails
Fixed module order, plan-aware feature flags, and configurable PII strategies — reduce drift between environments.
Data boundaries
Org-scoped provider keys, user-scoped cache and retrieval, and masking before payloads leave your policy boundary.
Observability
Per-run steps, cache hit types, RAG attribution hooks, and OTel — so incidents are short and audits are boring.
Getting started
From API key to governed rollout
1
FoundationConnect providers once, control access centrally
Register OpenAI, Anthropic, Google, or Mistral keys at org level. Applications call TokenSaver only, so provider credentials stay off app servers and client devices.
Outcome: one secure gateway for all teams and environments.
2
OptimizationSet smart defaults to reduce spend and drift
Define governed defaults for semantic cache, RAG, compression, and PII controls. Keep safe per-request overrides for advanced cases, without losing consistency.
Outcome: lower token cost, predictable behavior, faster delivery.
3
ScaleMonitor cost, quality, and security in real time
Track usage, spend, cache hit types, and step-by-step traces in one place. Detect anomalies quickly and provide audit-ready visibility for platform, security, and finance teams.
Outcome: confident rollout across products, teams, and providers.
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Frequently asked questions
What is an LLM gateway?
A single API and policy layer in front of multiple model providers. Your applications call TokenSaver; TokenSaver applies cache, retrieval, compression, and safety, then calls the right model with your org's keys.
Can I self-host?
The platform is designed for both cloud SaaS and self-managed deployments — keep data and keys inside your perimeter when required.
How does billing visibility work?
Runs record tokens, estimated cost, and cache outcomes so finance and engineering can reconcile usage without exporting raw logs.
Is the pipeline order fixed?
Yes — cache, RAG, compression, PII, then LLM, then metrics. That predictability is what makes debugging and compliance reviews tractable.