Kamba — Financial Analysis System
Financial Analysis System

From question to investment-grade work product. In one governed system.

Generic LLMs give you text. Kamba gives you finished, sourced, auditable work product — in minutes.

Connects to the data you already license
Market / vendor feeds
SEC / regulatory filings
Internal / proprietary data
Web / news sources
9:01 → 9:02  ·  work product ready
60% manual work removed
LIVE · ANALYSIS STREAM
H M L
Backtest · 24M+38.4% Δ
The problem
"My data is fragmented."
Internal systems, vendor feeds, filings, PDFs, emails, web — all separate. Every answer means hunting across all of them.
"My AI tools are not auditable."
Plausible but untraced. No source, no lineage. Nothing you can defend in an IC or a compliance review.
"My outputs are not reproducible."
Same question, different answer every run. Scheduled workflows and recurring reports are simply not possible.
Kamba fixes the workflow
"I need something that fixes the workflow, not just the answer."
Kamba connects the model to your data, permissions, validation layer, and review process. Work product your team can defend, repeat, and build on.
Why Kamba  →
Live work product

Not chat answers. Work product.

See all outputs  →
Data lineage

Every number traces to source.

Not a black box. Click any claim. Kamba shows where it came from — every source, every transformation, every timestamp.

Raw sources
BNP Paribas Q4 2025 Earnings Supplement
PDF · Table 3.2 · Filed 2026-02-05
EBA Risk Dashboard — Q4 2025
API · eba.europa.eu · Pulled 2026-04-22
Internal: 15-Bank Universe Master
XLSX · Proprietary · Updated 2026-04-20
Kamba operations
Extract & validate
CET1 pulled from Q4 supplement, Table 3.2, cross-checked against Basel III filing
Compute sector median
Median CET1 across 15-bank universe from EBA data, weighted by RWA
Δ
Delta calculation
Q4 vs Q3: 13.8% − 13.4% = +40bps sequential improvement
Work product claim
Investment Memo · European Banks
"BNP Paribas CET1 ratio improved 40bps to 13.8% in Q4 2025, outpacing sector median of 13.2%"

The model is the same. The difference is everything around it.

Get started

Send us a question you have asked a generic LLM. We will send back what Kamba produces.

Same question. Different system. The output is the argument.

Hedge funds · Asset managers · Insurance · Research teams