Unified view of AI flows
Agents, assistants, workflows and API calls in a single timeline.
Platform
One control plane for every AI flow.
TokenSaver instruments every LLM call, tool call and decision without changing your agents’ code: you see the fleet, you optimise the spend, you enforce policy before the model answers.
Observability
See what your AI agents really do.
Agents, assistants, n8n workflows and API calls consolidated in one readable timeline, with the agentic graph to follow every chain of calls.
Real-time metrics
Latency, cost, tokens, cache rate and guardrail failures, per agent, team or model.
Agentic hierarchy
Multi-agent call chains and the tools invoked at each step.
Signed, immutable traces
Every call logged, signed and exportable as OpenTelemetry for your audits.
Root-cause analysis
Trace a behaviour back to its origin with execution context and decision lineage.
Alerts & anomalies
Drift, cost spikes, injections and policy breaches caught before they become incidents.
Optimisation · FinOps
Your agents read less, and understand better.
Model selection, semantic cache and compression by content type, applied inside your business flows. You keep control of cost, quality and latency.
LLM cost reduction
Semantic cache, smart compression and routing to the most efficient model, without touching your agents’ code.
Controlled latency
Automatic failover to the fastest endpoints, optimised streaming and configurable quality thresholds.
Enterprise AI FinOps
Budgets per project, overrun alerts, per-team cost allocation and traceability of every euro spent.
Typical savings by content type
- JSON
- −70–90%
- Logs
- −80–95%
- RAG
- −40–70%
- Code
- −40–70%
- Diffs
- −40–60%
Varies by workload, measured per run. Reversible compression (CCR) lets the agent fetch the original on demand.
Cyber & Zero Trust
Secure every AI flow, before it leaves your perimeter.
Nothing is allowed by default. Every action is identified, governed by policy and traced. Your teams move faster with AI; your organisation keeps control.
Ungoverned AI flows are the blind spot of the IS.
Sensitive data leaks
Personal data, secrets and confidential information injected into prompts or returned by models.
Agent hijacking
Injection attempts that push an agent outside its business scope or trigger unplanned actions.
Over-powered tools
Agents with too much autonomy calling sensitive tools without validation.
Shadow AI
Unapproved models, connectors or integrations used outside the catalogue.
Zero visibility
No clear view of who did what, with which agent, on which data, at what cost.
A trust posture applied to every flow.
- 01
Never trust, always verify
Every AI call is authenticated and tied to an identity: user, application key or agent.
- 02
Default deny
Unapproved models, tools and connectors are refused. Only your approved catalogue flows.
- 03
Policies at the centre
Rules defined in the platform, per organisation, workspace or key, not in each client app.
- 04
Least privilege for agents
Allowed tools, bounded autonomy and human approval when needed.
- 05
Full visibility
Every decision, allowed, blocked or pending, leaves a trace for the SOC and the CISO.
Govern by policies.
Configure once, apply everywhere: chat, API, agents, MCP.
Sensitive data protectionAnti-injection guardrailsTool allowlistOutput handlingContent moderationSafe model routingCatalogue & approvalOpposable traceability
TokenSaver is not
- A simple model router
- A cost-only tool
- A chatbot
TokenSaver is
- ✓The layer that decides what may pass
- ✓That protects data inside the flow
- ✓That bounds agent autonomy
- ✓That proves what happened
Integrations
Keep your tools. Add the trust layer.
OpenAI and Anthropic compatible APIs, Python SDK, MCP tools or the open-source CLI: every entry point leads to the same control plane.
- Enterprise assistants & chat→
- LLM-compatible APIs→
- Agents & tool calls→
- MCP connectors→
- AI traffic outside instrumented apps→
Claude CodeCursorCodexLangChainLangGraphCrewAIn8nMakeZapierOpen WebUILibreChatLiteLLMAgentgateway
Frequently asked questions
Does TokenSaver replace my SIEM?+
No. It brings the missing AI layer (identity, policies, agent control and traceability) and exports its signals to your SIEM.
Do we need to change our AI tools?+
No. TokenSaver plugs into existing flows: chat, LLM-compatible APIs, agents, MCP connectors.
Who defines the rules?+
Your administrators and security teams, through centralised policies at organisation, workspace or key level.
How are autonomous agents handled?+
Least privilege: allowed tools, bounded autonomy, human approval steps when needed, and full traces of every decision.
From opaque AI to auditable AI.
Let us connect your existing flows in a few minutes.