EasyRouter

See it in action

Walk through a day with EasyRouter.

Pick a scenario and click through what each person actually does — from a budget that holds the line to a leaked key revoked without touching a line of code.

Interactive walkthrough · simulated data

Simulated

The problem

Enterprise AI spend is turning into an untraceable black box.

It's never a shortage of models. It's money you can't see and can't control — and these problems show up at the same time in nearly every company scaling AI.

On the bill

Runaway cost black box

Separate bills from every provider and no way to split spend by person, project or team. Spend you can't see is spend you can't stop.

No budget gates

No permissions upfront, no interception mid-flight. Budgets blow before anyone notices, and tracing takes days.

Fragmented bills, idle capacity

Incompatible bill formats across vendors, and no data on which provider keys and quotas sit unused.

Off the bill — often costlier

Key management chaos

API keys scattered across code, env vars and CI, often in plain text. Once leaked, impossible to trace or hold anyone accountable.

Compliance and audit gaps

No record of who sent what data to which model. When regulators ask, there's no evidence chain to produce.

AI asset drain

Top performers leave and their prompts, skills and know-how leave with them. Teams rebuild the same things again and again.

The first step of cost governance isn't cutting budgets — it's making every dollar of AI spend explainable, attributable and optimizable.

Cost governance

More than a clear AI bill — real, structural savings.

Visibility is the prerequisite, control is the baseline, savings are the outcome.

Step 1

See it

Where money goes, who spent it, and whether it was worth it.

Cost attribution & bill splitting across 6+ dimensions
Effect attribution tied to business output
One unified ledger across providers

Step 2

Control it

What shouldn't be spent, can't be spent.

Model, rate and spend limits — three layers stacked
Budget threshold alerts & blocking
Real-time circuit-breaking on anomalies

Step 3

Save on it

The same job done at a lower cost.

Smart routing: simple tasks to cost-efficient models
A/B testing for data-driven model selection
Key-pool allocation & idle quota reclaim

Four gates — before a request reaches a model

01

Who can call

RBAC + ABAC on your IAM / SSO. Everyone holds virtual keys only.

02

What they call

Model, rate and spend limits stacked at the source.

03

Over the line

Alert or hard-block at a threshold, say 90%, per team, project or key.

04

Abnormal spend

A burst of odd calls at 3 a.m. is stopped on the spot, not found at reconciliation.

ALLOWALERTAUDITINTERCEPTMASKROUTE TO APPROVAL

Value by role

One integration. Every role gets what it needs.

Architecture

Four layers: chokepoint · measurable cost · full audit trail.

Requests pass the control plane for policy and the execution plane for interception. Cost and usage data flow back the whole way — calls, cost and audit from one source.

Business call side

initiated as always — almost no code changes

Employee assistants · EasyCoding · CLI · business systems · MCP · agents · workflows · dev & test environments

Existing enterprise infrastructure

reused, never migrated

IAM / SSO · API gateway / service mesh · org permissions · network egress · cost centers · document systems

EasyRouter control plane

the brain of policy, cost & audit

Identity & access

Identity mapping · provider key pools · virtual keys · RBAC / ABAC · env & tenant isolation

Policy / cost / quality

Budgets · quotas · rate limits · routing fallback · cost attribution · key-pool allocation

Audit / risk / compliance

Compliance detection · PII masking · audit ledger · risk blocking · reporting

AI asset center

MCP / agent catalog · asset distillation · knowledge assets · retention · reuse

EasyRouter execution plane · Runtime Guard

the last gate before a call leaves

Local proxy / sidecar / gateway — identity check · PII detection & masking · key-pool selection · smart routing & fallback · circuit breaking · usage capture

AI capability egress

Public cloud models · private models · in-house inference · knowledge base / RAG · MCP / tools / agents / workflows

Deployment

Three integration forms — explicit, non-intrusive, fully equivalent governance.

Local proxy

developer-local

A CLI on the developer's machine. Change one Base URL in your CLI, IDE or scripts and you're in.

For: Dev & test, personal assistants, CLI workflows
Edge: Lightest onboarding, fast pilots

Sidecar

cloud-native

A container next to the service on the same subnet. Zero code intrusion, native fit for Kubernetes and service mesh.

For: Agents, microservices, containerized systems
Edge: Decoupled, low latency, elastic

Gateway

unified egress

All AI traffic through one gateway with built-in routing and load balancing.

For: Company-wide egress, centralized control
Edge: Configure once, effective everywhere

Non-intrusive

Keep your identity stack and gateways. Attach alongside an existing AI gateway, then switch over once you're confident.

No single point of failure

Not one gateway but a control plane: local proxies and sidecars run independently, so one failing never takes down the rest.

Private & air-gapped

Identity checks, masking, routing, quality detection and audit can all run on-prem — fully air-gapped operation supported.

★ Core module

EasyCoding — frontier-class AI coding, governed end to end.

A full autonomous coding agent that plans, edits, tests and ships — running entirely inside your governance perimeter. Every prompt, token and model call behind your engineers' code is visible, controlled and billed to the right team.

1Base URL, drop-in for IDE & CLI workflows

100%of coding AI calls governed & audited

0keys in plaintext on developer machines

One instruction in, a reviewed, tested pull request out.

Step 1

Understand & plan

Reads the ticket, the whole codebase and prior context, then writes a step-by-step plan before touching a file.

Step 2

Edit across files

Makes coordinated changes across dozens of files and stacks, respecting existing patterns, types and style.

Step 3

Run & self-fix

Runs the build and tests in a sandbox, reads failures and iterates until green — no human needed for routine work.

Step 4

Ship with full audit

Opens a PR with a clear diff and rationale. Every model call behind it already carries cost, identity and audit data.

Governance isn't a separate step — it's inline.The session that writes your code is already attributed to a team and repo, running inside budget, and fully logged.

IDE & CLI native

One Base URL, one key. No plugins to maintain, no agents to install.

Smart routing for code

Boilerplate goes to cost-efficient models, hard problems to frontier models. Quality dips trigger automatic fallback.

Code-aware budgets

Per-team and per-repo quotas with threshold alerts and hard stops. Engineering AI spend never surprises finance.

IP & compliance guard

Secrets and PII are masked before requests leave the machine. Prompt injection is detected and blocked inline.

Team knowledge flywheel

Best prompts, patterns and agent traces distilled into a shared library — new hires ship like seniors on day one.

Tackles Features from a spec Refactors & migrations Bug triage & fix Test generation Legacy modernization Codebase Q&A & onboarding

Beyond cost

Security · Compliance · Quality · Assets — governed on one foundation.

Same integration, same control plane. No separate system per domain, no repeated rework.

Security

Credentials & call behavior under control

Real API keys encrypted in the control plane; only virtual keys go out
Leaked keys revoked in minutes, keys or models swapped with zero code changes
Unauthorized and high-risk calls stopped before any model

Compliance

Full-chain trails, evidence on demand

SSNs, IBANs, passport and card numbers, emails and phone numbers masked before a request leaves
Who, when, which model, what data — export reports in one click
Custom packs: your sensitive words and masking rules, regex + intent
Prompt injection detected and blocked in real time

Quality

Success rate, latency and errors tracked into a performance baseline
Abnormal drift falls back to the stable version — the business never notices

Assets

People leave, the capability stays

Capture high-value sessions, MCP / skill chains and agent traces, scoped by admin
Distill into masked, versioned prompts, templates and capability packs
Reuse from one catalog with owners and approvals — callable from the CLI
Raw content stays on your side; only metadata is kept

Trust

Your data stays where you decide.

The answers your security, legal and procurement teams will ask for first.

Data residency

With private or air-gapped deployment, prompts, code and audit logs stay inside your own environment. Asset capture keeps raw content on your side and stores only metadata.

Compliance evidence

Every call is logged with who, when, which model and what data — the evidence trail GDPR, SOC 2 and EU AI Act reviews ask for.

Vendor review

Security questionnaire and data processing agreement available on request.

Certifications: TBC

Get started

Turn AI cost from a black box into a clear ledger.

The trial version is available to companies on request.

01

Email us from your work address

Tell us your company, how many engineers use AI tools, and what you want to try first.

contact@easycoding.codes Write the email

02

Receive your trial version

We confirm your company and send the trial build with a setup guide for your environment.

See it.Control it.Save on it.