Research & analysis
Literature review
Collect papers, index them and answer questions with citations.
- Store
- Search
- Graph
- AI
The scenario
A researcher points an agent at a topic. It gathers papers, indexes them, and answers follow-up questions long after the first pass.
How it works
- 1Papers are stored and indexed on arrival.
- 2Relationships between papers are recorded as a graph.
- 3Questions are answered from search results, with sources attached.
An illustrative scenario, not a customer story.
Interactive simulation
Simulate this case study
Watch the partition come up, each step run, and usage build as it goes. Simulated: volumes, timings and prices are illustrative.
Partition
—
Status
not created
Elapsed
00:00
- Provisioning
- Processing
- Complete
01Papers are stored and indexed on arrival.
queued- Ahura Storestore.putqueued
status: queued · 0 / 48 objects stored
- Ahura Searchsearch.queryqueued
status: queued · 0 / 520 documents indexed
02Relationships between papers are recorded as a graph.
queued- Ahura Graphgraph.edge.putqueued
status: queued · 0 / 380 edges recorded
03Questions are answered from search results, with sources attached.
queued- Ahura AIai.extractqueued
status: queued · 0 / 150 model calls
Services in this partition
Store
0 calls · 0.00 ACU
Search
0 calls · 0.00 ACU
Graph
0 calls · 0.00 ACU
AI
0 calls · 0.00 ACU
Spend by service
Event log
- Waiting to start.
Why Ahura OS
Why this is better on Ahura OS
A literature review is a long-lived asset, but most tooling treats it as a pile of files. Ahura OS stores each paper, indexes it on arrival, links it to related work in a graph and answers questions from the index with the source attached. Because storage, search, relationships and inference share one partition, nothing needs exporting between tools, and nothing is orphaned when the project ends. Freeze it and the entire library, with its index and links, waits at archive cost until the next study.
What each capability replaces
- Ahura StoreInstead of managing buckets, permissions and lifecycle rules, objects follow the partition: they freeze, thaw and expire with it.
- Ahura SearchInstead of running a search cluster, a managed, high-performance search engine indexes your content on write and queries it fast.
- Ahura GraphInstead of standing up and operating a graph database, relationships live beside your other state at the same price and isolation.
- Ahura AIInstead of a model gateway and several vendor contracts, one priced call reaches several models and chooses a cheap one when it can.
And on every use case
One endpoint, not a stack
Memory, storage, compute, inference, identity and messaging share one connection, one identity and one bill. The integration work you would normally own disappears.
Isolation by construction
Every agent’s world is a partition. Separation is how the platform is built, not a convention teams must remember to follow.
Cost follows use
Pay per call and per millisecond. Idle agents freeze to archive pricing. There is no capacity to reserve and nothing running unseen.
Retention and deletion built in
Lifetimes, expiry, freezing and destruction are platform features, so your data policy is enforced rather than aspirational.
Safe autonomy
Spending limits, protected signing keys, approval steps and signed actions let agents work unattended without being unaccountable.
Ready for audit
Designed against SOC 2 and ISO 27001 controls, with every call metered, recorded and attributable.
Compared
The old way of doing things
Reference managers, folders of PDFs and a search tool bolted on later. The index lives on one person’s machine and is lost when they leave.
Data retention is built in
Everything this scenario stores lives in one isolated partition with a lifetime you set. Expired data deletes itself, a paused project freezes to low-cost archive, and a finished one can be destroyed completely. Security and compliance