The Financial Analysis System
for Institutional Finance
Finished, sourced, auditable financial work product in minutes.
1.2 million institutional finance seats.
$2.9B market.
Every seat that produces or depends on governed financial work product.
1,227,000 seats globally
562,500 seats — reachable
38,000 seats · 150→38K ramp
Wealth Management · Investment Management · Hedge Funds · Corporations · Banks · Family Offices · Financial Research
Kamba turns questions and data into finished institutional work product.
Client-ready investment reports
Formatted, sourced reports delivered to advisors and clients — traceable to every underlying data point.
Investment committee memos
IC-ready analysis with full reasoning chain — defensible at the table, reproducible for compliance.
Portfolio and market exposure analysis
Efficient frontier, scenario comparison, risk diagnostics — across custodians, accounts, and positions.
Data quality reviews and backtests
DQRs and backtest reports with every assumption logged — built for audit and governance workflows.
AI can answer financial questions.
Institutions need defensible work product.
That work must survive:
Financial institutions cannot use answers they cannot source, audit, reproduce, and defend.
The missing layer is not another chatbot. It is governed financial work product.
Kamba built it.
AI is the commodity. The governed layer is not.
Kamba is the governed operating layer between approved data, frontier models, and institutional workflows.
Turning financial questions into sourced, reproducible, auditable work product.
| GENERIC AI | KAMBA |
|---|---|
| Draft answers | Finished financial work product |
| Unclear sources | Traceable numbers |
| Inconsistent outputs | Repeatable workflows |
| Manual data connections | Approved, licensed data access |
| One-model dependency | LLM-agnostic architecture |
| No institutional controls | Validation, lineage, governance |
Not the model. Not the terminal. Not the warehouse.
The execution layer that makes AI usable for institutional finance.
The output is the argument.
No staged walkthrough — these are real, live work products from kambagroup.com. Click through to open any of them.
European Banks — Credit Footprint & Portfolio Construction
15-bank long/short framework, 6-dimension scoring model, bull/base/bear scenario returns.
Open sample →Gold & GDX — Accumulation Thesis
Structured long thesis on gold equities with entry logic, catalyst timeline, and risk framing.
Open sample →Macro Rates Strategy — March 2026
Full rates thesis with curve analysis, validated data foundation, and forward projections.
Open sample →Buenaventura (BVN) — Analysis & Options Ideas
Fundamental and technical work with four defined-risk options trades and scenario-weighted returns.
Open sample →Brain Sentiment vs. Technical — Full Backtest
8-year backtest across 32 S&P 500 constituents comparing sentiment signals against technical strategies.
Open sample →NVDA Naked Puts — Options Income Screen
40-candidate OTM naked put screen ranked by annualized premium yield, 12–24 month expirations.
Open sample →Request a demo → kambagroup.com/get-in-touch · See all work product → kambagroup.com/usecases
Most enterprise AI startups spend years entering financial institutions.
Kamba starts inside them.
financial professionals on Symphony
Kamba's distribution base from day one.
PENETRATION
7,500 users
750K pros, 1,500 firms
$18–54M ARR
Kamba's own UI, API & MCP
Full UX control
via Be More Advisors
CRD# 284115
via Finalis
~1,000 partner clients
Symphony is one distribution wedge — institutional AI work product is the category.
Already inside named institutions.
Active / Onboarding
Advancing
Qualified contacts
Priced like Anthropic. Metered like modern SaaS.
Institutional buyers already procure AI and data infrastructure this way — seat-based subscription, usage-metered underneath. Kamba fits the shape.
per seat / month, sized to actual usage
per credit inside the bundle
2× bundle rate — incentivizes right-sizing
ARR from a single enterprise deployment · 600 users × $200/mo × 12
In One Line
The pricing shape institutional buyers already sign for. Anthropic, Snowflake, Databricks — seat-based subscription, usage-metered underneath. Kamba priced in credits that map to finished institutional work product. No pitch to change how the buyer buys.
Built by operators who know institutional finance.
Jean-Louis Lelogeais
Nicolas "Gucho" Aguzin
Sebastian Gunningham
+ 10 operators and investors
The product is built. Commercial channels are open. This bridge extends runway to a priced seed round, converting active institutional engagements into paid enterprise revenue.
Named institutions are already in pilots.
Last round priced ahead of conversion.
Comparable platforms (Rogo) valued at 100x+ SAM.
RAISED TO DATE $1.5M raised to date — this $750K bridge extends the round toward a priced seed.
Technical
42%Engineering, AI infrastructure, tools & platform hardening
Commercial
38%CEO & CTO time, sales, marketing & distribution partner activation
Operations
20%Fractional COO, legal, insurance, accounting & admin
Thank You.
Finished, sourced, auditable financial work product for institutional finance.