Spend less, get better answers, and own the models.
Foundry sends every request down its best-value path, brings your proven context to each prompt, governs every agent, and turns repeated work into models you own.
−50%+
typical AI-spend reduction once routing, enrichment and reuse stop you paying twice.
Modeled from routing, context reuse, cache hits and lower-cost model substitution vs a baseline provider mix.
Route work, bring approved context forward, build evals from reviewed outcomes, and promote a model only after it passes your tests.
Routing decision
Support escalation triage
Work Unit requirements
Candidate paths
Same task and evalQuality
91
Cost
$0.006
Latency
1.7s
Each Work Unit gets a route selected against policy, quality, and cost.
A living map of your org, with a memory that outlasts the session.
One layer: a queryable graph of people, tools and work, plus durable, scoped memory. Your people browse it in-app; your agents read and write it headlessly through the API and MCP, so nobody starts from zero.
- Queryable graph of people, tools & work
- Short- and long-term memory, scoped by team / project / permission
- In-app for people, API / MCP for agents, always current
Context & Memory
Pick the right model for the task, and enrich every prompt at run time.
Once Cortex has learned your org and its Work Units, it acts at run time: routing each request down its best-value path across models, tools and agents, and enriching the prompt with the relevant context before the model ever sees it.
- Routes across models, tools, agents & caches, best value per accepted answer
- Enriches every prompt with proven context from your graph & memory
- Permission-aware, fit to budget, inside your cost / latency / risk policy
Routing & Yield
Your own labeled datasets, benchmarks and evals, built from real work.
Cortex turns the work it captures into labeled datasets, benchmarks and evals unique to your org, your own Scale-AI-in-a-box. The training data and the yardsticks to judge a model are yours, generated continuously from what your teams actually do.
- Org-specific labeled datasets from real Work Units
- Benchmarks & evals tuned to your tasks, not generic leaderboards
- Continuously refreshed, and owned outright
Evals
Turn the work you repeat into a model you own.
Your real work is now training data. Atlas auto-labels every turn and pair, and Foundry ships specialized models you host in your VPC. Your IP compounds, and you stop renting it back.
- SFT & RL on your own data
- Models you own and host
- A compounding advantage, not a rented one
Model Tuning
Accepted Work Units → Corpus
Step 112.4M turns • Auto-labeled
SFT + preference pairs
Step 2Edits vs. Rejects as signal
Cortex-triage-v3 · Yours
OwnedHosted in your VPC
Ready to build sovereign intelligence?
Gain visibility and control. Build better, cheaper, faster AI that you own.