Fund performance and portfolio monitoring in one place
From first cheque to exit, D23 gives you live fund metrics (TVPI, DPI, IRR), portfolio company health signals, and LP-ready reports — all powered by managed Apache Superset connected directly to your data sources.
You know exactly where the day goes
- 1Fund metrics live in a spreadsheet that is always one update behind
- 2You find out a portco is in trouble at the board meeting, not three months earlier
- 3LP reporting is a quarterly fire drill stitching together data from a dozen sources
Reporting takes too long
Analysts spend days assembling reports that should refresh automatically from source data.
Data is siloed
Finance, operations, and sales all see a different number because no one has agreed on definitions.
Decisions lag the data
By the time a dashboard is ready, the window to act has already closed.
The numbers behind modern BI
You don't have to take our word for it. Here's what analysts and data teams are reporting right now.
60%
of data and analytics leaders say their BI tools are too complex for business users without SQL skills.
$28B
spent on Looker and Tableau licenses annually by enterprises — most of it for dashboards fewer than 20% of employees ever open.
3× ROI
median return on analytics investments reported by data-driven organizations within 12 months of deployment.
Most teams cut their BI cost by half and ship dashboards in days, not quarters.
D23 estimate, based on typical venture capital data-team workloads: hours saved on Superset ops, faster dashboard delivery, and self-serve analytics that no longer requires a dedicated analyst for every question. Your mileage depends on warehouse size and how many teams need access to data.
It already works at this scale
Not a demo. A team in the same kind of work, with results they published.
Nielsen
Financial Services · analytics
Nielsen migrated its enterprise BI stack to Apache Superset, reducing per-seat BI licensing costs by more than 60% and enabling its data teams to ship new dashboards in days instead of weeks.
60%+
BI licensing cost reduction
days
to ship a new dashboard
1 platform
replacing multiple BI tools
The strongest results come from teams with a connected warehouse, defined metrics, and dashboards their stakeholders actually use. That is exactly what D23 delivers.
Your venture capital dashboard suite
A set of managed Superset dashboards built for venture capital, each connected to your data sources and maintained by your D23 data team.
Fund Performance Dashboard
liveLive TVPI, DPI, IRR, and MOIC across vintages and investment stages, calculated from your cap-table and valuation data.
Portfolio Monitoring
livePer-company KPI cards tracking ARR, burn, runway, and headcount with configurable alert thresholds.
Deal Pipeline Analytics
liveFunnel velocity from sourcing through close, with conversion rates, cycle times, and partner attribution.
What D23 delivers
How D23 works in venture capital
- 1
Connect your warehouse
We connect to your venture capital data sources — Snowflake, BigQuery, Postgres, and 50+ others — in days.
- 2
Model your metrics
We define and agree on the metrics that matter — like Fund Performance Dashboard and Portfolio Monitoring — so every team uses the same numbers.
- 3
Ship your dashboards
We build managed Apache Superset dashboards with row-level security, SSO, and AI text-to-SQL built in.
- 4
Iterate together
Your D23 data team handles new requests, schema changes, and new data sources on an ongoing basis.
real-time
fund and portfolio metrics, no spreadsheets
Other industries
Private Equity
One source of truth across your entire portfolio
Financial Services
Treasury, risk, and compliance analytics on Superset
Healthcare
HIPAA-ready operational dashboards for healthcare teams
Insurance
Underwriting, claims, and loss-ratio analytics on one platform
Manufacturing
OEE, quality, and supply-chain visibility on Superset
Retail
Inventory, margin, and omnichannel analytics for retailers
Turn every team into a data team.
Get managed Apache Superset, the dashboards your business needs, and AI on top, without hiring a data team.