Where does TokenShift run?

Locally on the developer endpoint as a lightweight Go binary, no proxy, no access to code or credentials.

Do developers need to change their tools or workflow?

No. TokenShift works with the tools developers already use, no IDE plugins, code changes, or workflow updates.

Which coding agents are supported?

Claude Code, Cursor, GitHub Copilot, Devin Desktop, Codex, and additional agent frameworks.

How is it deployed and updated?

Distributed and updated centrally through your MDM, with auto-updates and zero-touch maintenance across every endpoint.

How much does TokenShift reduce token costs?

10–20% token reduction across 11 design partners with no change to how developers work. Structural waste is removed automatically before it reaches the model.

How is TokenShift different from an LLM gateway or proxy?

TokenShift runs locally on the developer endpoint as a lightweight Go binary. There is no proxy architecture, no central choke point, and no access to code or credentials. LLM gateways sit in the network path; TokenShift sits at the endpoint.

How long does TokenShift take to install?

Minutes. TokenShift is a single Go binary distributed centrally through your MDM with auto-updates, so engineers do not need to install or configure anything themselves.

Understand and control coding agent usage.

See how coding agents are used across your engineering organization, understand what's driving token spend, and manage them at scale. TokenShift gives engineering leaders a shared view across Claude Code, Cursor, Codex, GitHub Copilot, and the other coding agents already running across their developer fleet.

Supported coding agents

Claude Code
Cursor
Codex
GitHub Copilot

From token maxxing to value maxxing.

The first phase of coding agent adoption focused on increasing usage. The next phase is understanding where coding agents create value. Engineering organizations are increasingly asking:

Where are coding agents being used?
Which work is driving spend?
Which models are used for each type of task?
Where should teams invest more?
Where are clearer policies needed?

Answering those questions usually requires switching between provider dashboards, billing exports, and internal reports.

Everything you need to operate coding agents.

TokenShift collects usage metadata from endpoints across your organization and brings it into one console.

TokenShift console showing cost, performance, and budget panels with top spenders by coding agent

Visibility

Understand coding agent adoption across your entire organization.

Coding agents
Models
Users
Repositories
Projects
Sessions

Cost

Understand what's driving token spend.

Token usage
Approximate spend
Repository attribution
Cost drivers
Work classification

Assets

Know what's deployed across the fleet.

Endpoint inventory
Fleet health
MCP inventory
Tool inventory
Hook status

Governance

Manage coding agent usage across the organization.

Role-based access
Budget guidance (landing this week)
Capability guidance (coming soon)

Why TokenShift.

One view across multiple coding agents

See usage across Claude Code, Cursor, Codex, GitHub Copilot, and other supported coding agents in one console, instead of a separate dashboard for each.

Usage tied to any work

Every session is classified by the type of work it represents and attributed to its repository or project, so a dollar or token total can be traced back to feature work, debugging, or research.

Visibility from the endpoint

TokenShift captures the context that model-provider dashboards cannot see, including the coding agent, project, repository, tools, session, and device.

Deployment across the fleet

Roll out one native agent through MDM. New coding agents and models are supported without additional rollout effort or per-endpoint setup.

How it works.

1
Deploy
Roll out the native TokenShift agent through your existing MDM platform.
2
Classify
Sessions are classified locally on each endpoint.
3
Collect
Usage metadata is sent to TokenShift. Prompt content remains on the endpoint, and there is no model call in the request path.
4
Understand
Engineering leaders get one view across coding agent usage, token spend, work classification, inventory, and fleet health.

Evaluate TokenShift in your environment.

Start evaluating TokenShift using your own developer fleet. A typical proof of concept includes:

MDM deployment

MDM deployment to a defined group of developers.

Coverage validation

Validation of endpoint and coding-agent coverage.

Usage review

Review of usage, spend, work classification, and inventory.

Next steps

Definition of the next governance or optimization use case.

See how TokenShift helps engineering organizations understand coding agent usage, identify what's driving token spend, and establish the foundation for governance across their developer fleet.

The missing control layer for AI-assisted development.

TokenShift sits between your team and their coding agents, giving security, finance, and platform teams full visibility and control over every AI interaction, across Claude Code, Codex, Cursor, Copilot, and Devin Desktop.

Governance and compliance. Control which models, tools, and MCP servers are allowed, and what data can leave the endpoint.
Cost visibility. See exactly what AI is costing the business, broken down by team, project, and model.
Token optimization. Reduce token cost 10–20% by optimizing context, not downgrading models.
Full auditability. Every interaction is observed, logged, and enforceable by policy.