Kamba Analyst · Use Cases

What Kamba Analyst actually does for data teams.

Each workflow below is a real pattern we see at hedge funds, asset managers, and banks—where months of manual work are compressed into a single, repeatable flow.

Use this page to align stakeholders: data strategy, sourcing, quants, PMs, procurement, and compliance. Each section covers pain points, how users interact with the analyst, and why the workflow matters.

Data Quality

2. Data Quality Audits

02

Pain Points Solved

  • Manual quality checks are inconsistent and time-consuming.
  • Firms struggle to compare vendors objectively.
  • Compliance audits require repetitive, manual documentation.
  • Onboarding stalls due to lack of standardized evaluation.

User Input

  • Vendor name or domain.
  • Sample dataset or data dictionary.
  • Coverage expectations.

AI Actions

  • Run automated DQR (Data Quality Report).
  • Benchmark vendor coverage and highlight anomalies.
  • Document compliance-ready reports.
  • Compare vendors side-by-side.

Why This Is Revolutionary

  • Standardized Evaluation: Replace manual reviews with automated workflows.
  • Faster Procurement: Reduce vendor onboarding time drastically.
  • Compliance-Ready: Generate audit documentation automatically.
  • Compare at Scale: Evaluate multiple vendors with consistent metrics.
Backtesting

3. Instant Backtesting

03

Pain Points Solved

  • Backtests require engineering resources and custom coding.
  • Analysts wait days or weeks for validation results.
  • Hard to compare multiple datasets/strategies side-by-side.
  • Results are often opaque with little explanation.

User Input

  • Test Strategy A across the last 3 years.
  • Compare Dataset X vs. Dataset Y on signal strength.
  • Visualize alpha decay or Sharpe changes over time.

AI Actions

  • Select timeframes, benchmarks, and parameters.
  • Build and execute backtest logic.
  • Visualize returns, drawdowns, signal decay, and more.
  • Explain results in plain language.

Why This Is Revolutionary

  • Instant Backtesting: Validate signals or datasets in seconds—no coding required.
  • Compare Alternatives: Evaluate multiple datasets or strategies at once.
  • Explain the “Why”: Understand logic behind results, not just output.
  • Visual + Narrative Output: Get clear charts and explanations together.
Procurement

4. Procurement Support

04

Pain Points Solved

  • Procurement cycles stretch for months with fragmented communication.
  • Buyers and vendors lack visibility into process status and missing requirements.
  • Manual paperwork and contract handling create bottlenecks and errors.
  • Policies are inconsistently enforced, exposing firms to compliance risk.

User Input

  • Vendors of interest, use case, data needs, budget, and contractual constraints.
  • Risk/compliance requirements (PII, residency, usage rights) and desired timelines.
  • Custom firm-specific policies, forms, and templates.

AI Actions

  • Act as a two-sided assistant connecting buyers and vendors directly, facilitating secure conversations and progress updates.
  • Message both sides with status (missing documentation, next steps, completed tasks, policy exceptions).
  • Provide pre-formatted forms for vendors to complete and return; validate submissions against firm policy.
  • Customize procurement agents to firm requirements: workflows, compliance checks, escalation rules.
  • Generate diligence checklists, RFPs/RFIs, POCs, and ROI scenarios seamlessly.

Why This Is Revolutionary

  • AI as Assistant: A digital procurement partner guiding both sides step-by-step.
  • Two-Sided Messaging: Vendors and buyers stay in sync on status and blockers.
  • Policy Enforcement: AI flags missing docs, out-of-policy terms, or incomplete submissions instantly.
  • Customization: Workflows, forms, and logic match internal processes.
Data Insights

5. Data Insights & Business Answers

05

Pain Points Solved

  • Analysts spend hours stitching together answers from multiple data sources.
  • Key business questions often span both structured and unstructured data.
  • Metrics are not standardized, leading to inconsistent answers.
  • Stakeholders lack quick, trusted insights during decision-making.

User Input

  • “What’s the current multiple for NVIDIA?”
  • “How much liquidity does Fund X have, and when is the next redemption window?”

AI Actions

  • Identify key financial concepts.
  • Search structured (e.g. Snowflake) and unstructured (e.g. PDFs) sources.
  • Apply business logic and interpretation rules.
  • Return synthesized, calculated responses.

Why This Is Revolutionary

  • Query Any Source: Ask natural-language questions across data lakes.
  • Contextual Understanding: Recognize business intent and deliver precise answers.
  • On-the-Fly Metrics: Combine data and compute custom metrics instantly.
  • One Interface: Eliminate data digging and siloed workflows.
Reporting

6. Executive Reporting

06

Pain Points Solved

  • Reporting teams spend days consolidating and formatting spreadsheets.
  • Executives and regulators need fast, reliable updates.
  • Manual reporting introduces risk of human error and version conflicts.
  • Lack of audit trails creates compliance exposure.

User Input

  • Report type (e.g. NAV, compliance summary).
  • Portfolio, timeframe, audience.

AI Actions

  • Generate reports using templates.
  • Format for internal or external use.
  • Schedule delivery or automate distribution.
  • Preserve audit trail and versioning.

Why This Is Revolutionary

  • No More Manual Reporting: Eliminate spreadsheet workflows.
  • Instant Distribution: Deliver to executives or regulators with one click.
  • Template-Based Output: Ensure formatting and language consistency.
  • Fully Auditable: Retain history of all versions and recipients.
Collaboration

7. Team Collaboration

07

Pain Points Solved

  • Teams duplicate work due to poor coordination.
  • Approvals and version control are fragmented across emails and files.
  • Key stakeholders miss updates without proper alerts.
  • Collaboration tools are not integrated with compliance and audit needs.

User Input

  • Research prompt or reporting task.
  • Collaboration request between teams.

AI Actions

  • Secure prompt sharing inside Symphony.
  • Role-based access to data and outputs.
  • Preserve version history and approvals.
  • Trigger alerts or workflow actions.

Why This Is Revolutionary

  • Unified Workspace: Central hub for collaboration across research, compliance, and data.
  • Custom Access Levels: Control who sees what — by role or department.
  • Built-In Alerts: Notify stakeholders at key milestones.
  • Full Traceability: View who contributed what, when, and why.
See these use cases live on your own data.
We’ll run Smart Search, a DQR, and a backtest on a dataset you care about so stakeholders see the full workflow end-to-end — in minutes, not months.
Best for data strategy, sourcing, quant leads, and PMs evaluating new data or fixing current workflows.