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Vaedra: The Research Platform for Analysts

Vaedra runs onfrontier models
OpenAI
Claude
Gemini
Grok
Qwen
Kimi

Slow research kills edge.Vaedra solves both.

Without Vaedra

Context is fragmented

Filings, notes, transcripts, and market signals sit apart from the claims they support.

Reasoning is hard to audit

Teams need a clear trail from source material to conclusion, including what changed and why.

Review needs a durable record

Approvals, holds, and judgment calls should preserve the evidence beneath every decision.

Coverage notes
Scattered across 11 tabs, 3 apps, 2 notebooks.
ticker · MSFT
Cross-coverage
Implications traced manually, paper by paper.
thread · semis
Follow-up lag
No persistent memory between sessions.
queue · 14d
Thesis drift
Yesterday's reasoning is already stale.
last read · 4d
Context decay
The model forgets everything when the chat ends.
session · closed
Slow idea generation
Tedious compliance tracing
With Vaedra
NVIDIA
8-K Filing
NVIDIA
Revenue
$68.1B
Data Center revenue
$62.3B
Diluted EPS
$1.76
GAAP gross margin
75.0%
Review Filing
Relationship Map
Suppliers14
Partners27
Customers31
NVIDIA
TSMC
NVIDIATSMC
Relationship
Foundry partner
Signal
Capacity dependency
Relevance
Critical
View Connection
NVIDIA
Microsoft
NVIDIAMicrosoft
Relationship
Cloud partner
Signal
Compute demand
Relevance
High
View Connection
Analyzing Connections
Previous HypothesisNVIDIA
Hypothesis
Data center assumption
Source
Analyst Memo
NVIDIAData center assumption from Analyst Memo
Confirmed by 8-K
NVIDIA
NVIDIA
Data Center Assumption
Hyperscaler capex inflects
Bullish
Key buyers
MicrosoftAmazonGoogle
Street underestimates
DC re-acceleration
Supply chain bottlenecks
From analyst memo
Review Hypothesis
Ingestion

Files enter the pipeline.

Filings, spreadsheets, source notes, and company feeds become normalized records before research begins.

Evidence graph

Evidence becomes structure.

Signals connect to entities, claims, and prior work so an investigation can be understood at a glance.

Synthesis

Evidence becomes synthesis.

Vaedra reconciles the implication path, separates signal from noise, and turns evidence into an analyst-ready view.

Research brief

The output feels finished.

A concise research brief carries the answer, evidence trail, and open questions into the next decision.

01Ingestion 02Evidence graph 03Synthesis 04Brief

Mission control

live desk
NVIDIA GB300 supply chain implications 14 entities traced / 3 pending gates / updated 09:42
active
Apple supplier migration and margin pressure 8 entities traced / 1 pending gate / updated 09:36
active
CoWoS pricing curve and HBM allocation 12 entities traced / Taiwan layer linked
queued
481kg nodes
882edges
1,719events
58workflows
TSMC revenue beat connects to CoWoS utilization.
Foxconn India ramp data ingested into Apple supplier model.
Blackwell shipment cadence affirmed; GB300 sampling window moved.
High-NA EUV delivery timing now one quarter softer.

Signal intake

extracting
Cloud TPU capex language added to hyperscaler cluster.
AWS Trainium deployment scope updated from supplier logs.
Azure power contract maps to 2027 data center buildout.
Rack integration pressure routes into GB200 cluster timeline.
EUV tool constraint tagged as upstream gating dependency.
93%entity resolution
24new aliases

Knowledge graph browser

dependency map
NVIDIA TSMC ASML

Orchestrator run

tracing consequences
00:01Opened NVIDIA shipment cadence hypothesis and retrieved upstream memory dependencies.
00:18Linked CoWoS capacity note to Apple margin sensitivity and cloud capex cluster.
00:37Raised confidence on HBM constraint; generated alternate supplier path.
01:04Compiled analyst-facing delta with source walkback and open questions.

Agent confidence

Morning brief

ready

SEMI cycle turn / AAPL implication

Inventory is now above the five-quarter baseline while supplier commentary points to uneven HBM allocation. The model recommends revising margin pressure assumptions into Q4.

EntitySignalConf.
SK HynixHBM3E pricing negotiations moved hotter.0.91
TSMCCoWoS capacity remains the binding constraint.0.87
AppleSupplier mix raises margin sensitivity.0.72

Who Vaedra is For

Lean research teams
For teams stretched thin, wanting greater coverage with fewer resources.
Solo analysts
For individuals who need help expanding their investment-grade research.
Research-intensive firms
Edge built from investigative depth, and enabling increased collaboration.
Institutional Advisors
Investment managers who need to see the high-level information for overall market shifts.
See how Vaedra fits underneath your desk

Access tiers built for serious research.

Analyst
For the solo researcher building edge.
$500/ mo · analyst
  • Up to 50 monitored entities
  • 5 active workflows
  • 90-day memory depth
  • Core investigation tools
  • 1 seat
  • Email support
Request access
Recommended
Team
For research desks that need shared reasoning.
$450/ mo · analyst
  • Up to 200 monitored entities
  • 25 active workflows
  • 1-year memory depth
  • Advanced investigation tools
  • Up to 10 seats
  • Shared reasoning graphs
  • Priority support
Request access
Enterprise
For institutions requiring full operational control.
Custom
  • Unlimited monitored entities
  • Unlimited workflows
  • Full historical memory
  • Geospatial layer, full depth
  • Unlimited seats
  • Custom integrations
  • Dedicated support
  • On-premise option
Request access
Get started

Turn research into institutional memory.

Vaedra helps research teams connect signals, preserve context, and act on what matters, before the market fully prices it in.

ACTIVE RESEARCH STREAM
Q2 coverage · 4 signals
Live
AAPLEarnings revisionMonitored
FEDRate path · Q2 stanceLinked
SEMIInventory cycle thesisFlagged
MEMOPortfolio brief · Q2Generated
vaedra · reasoning graph14:32 ET