Research AI Infrastructure (RAI)
Research assistance that makes support, disagreement and uncertainty inspectable.
An answer should carry its evidence, not just its confidence.
What RAI is for
Research AI Infrastructure is an independent project for research assistance that can show the source basis of an answer. Its design includes document retrieval, research memory, evidence attribution, contradiction handling and deterministic calculation tools.
The challenge is to preserve useful answers without letting fluent language conceal missing support. A source disagreement, an unsupported claim and an incorrectly attributed observation require different treatment.
Trace a claim to its exact evidence
Independent public demonstration · Authored fictional passages. Retrieval, attribution, comparability, and support are separate checks.
Source A: business credit in February. Source B: household mortgages in February. Inspect their scopes before combining them.
Fictional lending survey A
A:p1 · February · business credit
In February, respondents reported tighter conditions for business credit.
Not directly comparable
The sources describe different markets. Their observations do not establish a joint trend.
Answer after inspecting the evidence
Source A describes business credit; source B describes household mortgages. Report their observations separately.
This evaluates structured public example records, not arbitrary prose or source truth. The private RAI system does not run here.
What I work on
- Evidence-aware research
- Connect findings to source material, preserve transformations and make missing coverage visible.
- Contradiction and uncertainty
- Keep conflicting observations distinct and explain what additional evidence could change an assessment.
- Replaceable components
- Separate enduring research records from a particular model, provider or retrieval implementation.
- Bounded tools and integration
- Keep a research recommendation separate from permission to invoke a tool or change another system. A future CR interface remains an independent, governed boundary.
A decision that matters: keep the disagreement
Two reports can disagree because they measure different things, cover different periods or contain an error. Merging their wording into a confident conclusion can erase the very distinction a researcher needs to inspect.
The evidence inspector preserves the source passages and their scope. Leaving a source out produces a coverage gap; assigning an observation to the wrong source produces an attribution problem. Agreement is evaluated only after those checks pass.
Useful assistance without borrowed authority
A research layer can help organize evidence and propose a next question. That does not make it the owner of scientific calculations, operational permissions or deployment decisions. RAI is designed to remain independently governed rather than silently becoming part of CR.
The implementation and its historical checks are separate from activation of a live research service. I do not present this portfolio animation as an autonomous research agent.
The connection to security analysis
In my independent packet lab, DNS failures and an HTTP POST are observations worth investigating. They do not, by themselves, establish command-and-control or data theft. RAI addresses the same distinction between evidence, interpretation and a justified next step.
Scope and evidence
Public architecture summary of private research software. The interactive examples trace structured fictional records; it does not verify arbitrary source truth. No live RAI/CR integration, autonomous SOC effectiveness or production reliability is established here.