Financial data workflows —
from months of grind
to minutes of output.
Kamba is the operational layer that turns sourcing, validation, backtesting, procurement, and reporting into automated, auditable workflows — embedded where your team already works, without moving your data.
Your teams are brilliant. Your workflows are the bottleneck.
Finance data teams don't lack talent — they lack operational leverage. Sourcing the right dataset takes weeks. Validating quality is manual and inconsistent. Backtesting requires engineering queues. Procurement drags for months. Reporting is a spreadsheet grind with audit risk baked in.
Kamba replaces all of that with a single AI-native workflow system: built for CIOs and heads of data who are done funding sandboxes, disconnected tools, and months-long onboarding cycles. It runs on top of your existing stack, surfaces inside Symphony or your own UI, and produces governed, auditable decision artifacts — without touching your data residency.
Runs on your Snowflake, S3, and vendor feeds. No shadow copies. No data movement.
Governed by design
Entitlements, prompts, and outputs respect existing roles, compliance, and audit requirements.
Surfaces in Symphony or any front-end your teams already use. No new portal to enforce.
Estimate the annual drag from workflow friction
An illustrative planning model for CIO and data leadership. Quantify potential impact from reducing capacity waste, vendor waste, and decision latency.
See Kamba Analyst do the work
Three short clips. No promo fluff. Just the core workflows your teams care about.
Ask in plain language. Surface relevant internal and external datasets in seconds.
Open clip →
Coverage, gaps, anomalies, and stats in a structured view from a raw sample.
Open clip →
- One prompt scopes the request across internal and external data sources.
- Returns ranked dataset candidates and an auto-generated dataset brief.
- Standardized quality checks with issues logged and mitigations documented.
- Hard gate: failed datasets stop here — no wasted evaluation downstream.
- Continuous drift/decay monitoring once a dataset is approved.
- Explicit assumptions and reproducible methodology.
- Auto-codes, validates, and stress-tests strategies within firm-defined guardrails.
- Designed for IC, Risk, and Procurement review — not one-off notebooks.
- Approved, versioned artifacts with full lineage attached.
- Deep-dive domain reporting: investment, insurance & credit, risk, regulatory.
- Designed for reuse, monitoring, and refresh — not rebuild.
- All validated outputs stored, versioned, and governed — not scattered across notebooks.
- Approvals & permissions: role-based access control per team and room.
- Full lineage: every artifact traces back to source data and analyst.
- Audit trails: every decision logged — defensible months or years later.
- Reuse: approved evidence accelerates future decisions instead of rebuild.
Built for workflows that drive outcomes
Click through to the Use Cases page for the full breakdown.
Centralize requests, samples, comparisons, and diligence so teams stop repeating work across disconnected tools.
Reduce friction from dataset to tested signal with repeatable checks, instant backtests, and explainable outputs.
Make outcomes reusable across teams with governed sharing, traceability, and versioned decision artifacts.
Not another portal. An analyst that does the work.
The operational layer that compresses time to decision, reduces waste, and keeps AI usage auditable — without re-platforming your stack.
Every workflow ends in a governed, reusable artifact — not a notebook only one analyst can read.
Connects to Snowflake, S3, vendor feeds, and internal docs. No shadow copies. No new data warehouse to manage.
Entitlements, logging, prompt auditability, and role-based access align with compliance and risk requirements from day one.
Put Kamba Analyst in front of your data
If your teams are still stitching workflows together with email, tickets, and ad hoc notebooks — it's time to see Kamba on your stack.
- Heads of data and data strategy — compress delivery cycles and reduce vendor waste.
- Data sourcing and vendor teams — standardize evaluations and onboarding.
- PMs and quant leads — validate whether data and signals add P&L.
Place your Squarespace Form block here. Keep it short: name, firm, role, email, and one sentence on your workflow.
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