SAGE
Stratus Agentic Generation Engine
SAGE is the foundational engine powering all NeuroQuest Labs products. A unified framework where agents exist persistently, maintain deep memory across interactions, learn from mistakes, and operate autonomously on complex tasks.
The foundation
One engine. Three guarantees.
Autonomy
Agents decide what to do next on their own. They plan, act, verify their work, and recover from failure, looping until the goal is met.
Read the research→Memory
Powered by Lattice, agents keep deep memory across sessions with a source-validated graph, so the system grows more intuitive the longer you work with it.
Explore Lattice→Control
Every action is checked against policy before it runs. Scoped permissions, sign-off gates, and full audit trails keep autonomy inside the limits you set.
Talk to us→What the engine can do
Six capabilities that make SAGE agents autonomous, durable, and safe at scale.
Recursive Agentic Loop
Agents that think, plan, and self-correct.
- ✓Drafted summarystep 1
- ⚠Self-review: missing budgetcaught
- ↻Re-read transcript, revisedpass 2
- ✓Summary approveddone
Persistent Memory
Every interaction makes the system smarter.
- ✦Client prefers Friday check-insrecalled
- •Acme contract renews in March2 mentions
- •Q3 budget approved: $50klast week
- •Primary contact: Dana Leefrom CRM
Multi-Agent Orchestration
Complex problems, specialized solutions.
- Researcherrunning
- Analystrunning
- Writerqueued
- Fact-checkerdone
Intelligent Context Management
Coherent understanding at any scale.
- Meeting notes12k
- Conversation88k
- Reference docs62k
- ⤓Older turns compacted−40k
Custom Tool Integration
Connect anything, automate everything.
Asanatrack tasks
Airtablequery records
Figmaread designs
Miromap ideas
Loomsummarize clips
Enterprise Safety Rails
Autonomous, within the boundaries you define.
- ✓Look up account balanceallowed
- ✓Send status updateallowed
- ❙Issue $1,200 refundsign-off
- ✕Export customer listblocked
Memory engine
Lattice
Lattice is SAGE's persistent memory: source-validated extraction, a typed memory graph, and multi-signal retrieval. It is where an agent stops repeating questions and starts knowing you. In 1.10, the focus moved from finding the right memory to using it correctly.
Deterministic recall
Counting and date arithmetic are computed in code, not guessed by the model.
Subject-aware updates
The current value always wins, and distinct subjects never overwrite one another.
Dual-surface memory
Distilled facts alongside verbatim context, so nothing said is ever lost.
- ✦Client prefers Friday check-insrecalled
- •Acme contract renews in March2 mentions
- •Q3 budget approved: $50klast week
- •Primary contact: Dana Leefrom CRM
New in 1.10
Three new layers
Context Engine
Fits any input to the model's budget. Retrieval indexing, map-reduce, and a content router route document sets, large tool results, and long histories into context without losing the part that matters.
End-to-End Tracing
Every operation emits a back-traceable span. Walk from any output to its root through the operations, timings, and token costs that produced it. OpenTelemetry-native, and off by default.
Concurrency-Safe Writes
A pluggable lock serializes the memory write path, so concurrent agents never duplicate a fact or lose an update. Correct on a single node, and ready for a fleet.
Build on SAGE
The engine behind
everything we build.
Use it through our products, or talk to us about a custom agent running on the same engine.