Modernize without rewrites
Replace data systems, gateways, and runtimes behind stable interfaces instead of rebuilding every dependency.
Eden gives platform engineering teams a practical control layer for upgrading data, gateways, and runtime infrastructure while the business stays online.
Replace data systems, gateways, and runtimes behind stable interfaces instead of rebuilding every dependency.
Use live capture, replay, and operational evidence to understand the change before it becomes irreversible.
Carry rollback state, policy, and the record of every decision with the same workflow from start to finish.
The modernization workflow
Eden turns a dangerous all-at-once project into observable stages: connect the current system, prove the next state with real traffic, then advance with recovery ready.
Bring current runtimes, data systems, and policy boundaries into one view.
Capture, replay, compare, and validate without taking production offline.
Move only when the result and recovery path are visible to the team.
What is already serving customers.
Evidence and recovery stay with the change.
The new system advances when it is ready.
Production capabilities
Adopt what the next stage needs—AI, storage, data gateway, modernization, operations, or security—while keeping one operating model around the work.
Run inference, discover marketplace capacity, operate agent fleets, route models, ground answers with RAG, and train governed models.
Run the storage primitives your applications and AI depend on, in the infrastructure you control.
Act on data across systems with gateways, APIs, workflows, transactions, and shared context.
Plan, test, move, validate, cut over, and recover production systems without a blind migration.
Understand production, optimize behavior, investigate incidents, and operate fleets, costs, telemetry, and deployments.
Protect AI, agents, data, identities, credentials, policy, approvals, evidence, and private connectivity.
Performance you can inspect
Eden is built to make production systems easier to change—and to keep the controls fast enough to belong in the critical path.
Controlled results are workload-specific, not universal capacity claims. Review the method and source behind every comparison.
Benchmark results
Direct results with named baselines or workload context.
Gateway / Redis
Gateway / PostgreSQL
Gateway / PostgreSQL
Gateway / MongoDB
Gateway / AI Gateway
Gateway
Database
Telemetry
Key-value / ShardKV
Key-value / ShardKV
AI Gateway
What modern teams get
Route services, models, and data through policy, observability, and controls that stay close to the work.
Upgrade databases, caches, streams, and storage without coupling the change to application downtime.
Put inference, agents, context, and tools behind the runtime controls production teams need.
Give teams evidence for performance, cost, access, incidents, and recovery across every environment.
Modernize on your terms
Start with one system, prove the change against real traffic, then bring the same control model to the rest of the stack.