Every metric.Every anomaly.One live canvas.
DataSwain unifies your warehouses, apps and event streams into one governed lakehouse — then watches it around the clock, surfacing drift, anomalies and revenue signals long before they reach your P&L.
- AWS-native lakehouse
- SOC 2-aligned controls
- Live in six weeks
Revenue intelligence
14 sources unified · refreshed 42s ago · last 30 days + forecast to 14 days
Net revenue
$11.7M
+14.2%vs prev 30 days
Blended ROAS
4.12x
+8.7%vs prev 30 days
Pipeline freshness
48s
-22.5%vs prev 30 days
Anomalies open
7
-31%vs prev 30 days
Net revenue
Daily, last 30 days
| Period | Net revenue by day |
|---|---|
| Aug 11 | $303,015 |
| Aug 12 | $308,097 |
| Aug 13 | $306,125 |
| Aug 14 | $310,555 |
| Aug 15 | $324,159 |
| Aug 16 | $337,875 |
| Aug 17 | $334,462 |
| Aug 18 | $325,132 |
| Aug 19 | $323,646 |
| Aug 20 | $333,405 |
| Aug 21 | $328,880 |
| Aug 22 | $325,416 |
| Aug 23 | $328,194 |
| Aug 24 | $334,463 |
| Aug 25 | $344,505 |
| Aug 26 | $370,779 |
| Aug 27 | $368,361 |
| Aug 28 | $371,736 |
| Aug 29 | $385,459 |
| Aug 30 | $396,150 |
| Aug 31 | $391,360 |
| Sep 1 | $392,081 |
| Sep 2 | $399,207 |
| Sep 3 | $397,989 |
| Sep 4 | $383,508 |
| Sep 5 | $401,943 |
| Sep 6 | $398,943 |
| Sep 7 | $410,684 |
| Sep 8 | $419,474 |
| Sep 9 | $410,192 |
Workload mix
Share of compute
- Streaming41%
- Batch ELT27%
- Reverse ETL19%
- Ad-hoc13%
| Segment | Value | Share |
|---|---|---|
| Streaming | 41 | 41% |
| Batch ELT | 27 | 27% |
| Reverse ETL | 19 | 19% |
| Ad-hoc | 13 | 13% |
Revenue forecast
Observed tail joined to the modelled next 14 days
- Observed
- Forecast
- 80% interval
| Period | Net revenue observed and forecast, next 14 days | Basis | 80% interval |
|---|---|---|---|
| Aug 25 | $344,505 | Observed | — |
| Aug 26 | $370,779 | Observed | — |
| Aug 27 | $368,361 | Observed | — |
| Aug 28 | $371,736 | Observed | — |
| Aug 29 | $385,459 | Observed | — |
| Aug 30 | $396,150 | Observed | — |
| Aug 31 | $391,360 | Observed | — |
| Sep 1 | $392,081 | Observed | — |
| Sep 2 | $399,207 | Observed | — |
| Sep 3 | $397,989 | Observed | — |
| Sep 4 | $383,508 | Observed | — |
| Sep 5 | $401,943 | Observed | — |
| Sep 6 | $398,943 | Observed | — |
| Sep 7 | $410,684 | Observed | — |
| Sep 8 | $419,474 | Observed | — |
| Sep 9 | $410,192 | Observed | — |
| Sep 10 | $419,611 | Forecast | $407,023 – $432,199 |
| Sep 11 | $421,967 | Forecast | $404,455 – $439,479 |
| Sep 12 | $418,613 | Forecast | $396,427 – $440,799 |
| Sep 13 | $415,009 | Forecast | $388,241 – $441,777 |
| Sep 14 | $409,600 | Forecast | $378,470 – $440,730 |
| Sep 15 | $413,127 | Forecast | $376,978 – $449,276 |
| Sep 16 | $419,987 | Forecast | $378,408 – $461,566 |
| Sep 17 | $431,443 | Forecast | $383,769 – $479,117 |
| Sep 18 | $434,590 | Forecast | $381,570 – $487,610 |
| Sep 19 | $430,339 | Forecast | $372,889 – $487,789 |
| Sep 20 | $427,089 | Forecast | $365,161 – $489,017 |
| Sep 21 | $420,555 | Forecast | $354,738 – $486,372 |
| Sep 22 | $426,478 | Forecast | $354,830 – $498,126 |
| Sep 23 | $435,438 | Forecast | $357,277 – $513,599 |
Predicted outcomes
Ranked by modelled likelihood
- Quarter revenue target metrevenue_v7 · 14-day horizon87%
- EU checkout churn spikedriver: latency p95 · 7 days64%
- Paid search CAC over capdriver: auction density · 10 days41%
- Warehouse spend overrundriver: ad-hoc query volume23%
Revenue by channel
One hue per channel, last 30 days
| Category | Revenue by acquisition channel |
|---|---|
| Paid search | $3,420,000 |
| Organic | $2,880,000 |
| $1,940,000 | |
| Marketplace | $1,610,000 |
| Retail | $1,180,000 |
| Affiliate | $690,000 |
Checkout latency
Against the learned expected band
- Observed
- Anomaly flagged
| Point | Value | State |
|---|---|---|
| #1 | 1,142 | Normal |
| #2 | 1,047 | Normal |
| #3 | 1,101 | Normal |
| #4 | 2,228 | Anomaly |
| #5 | 1,129 | Normal |
| #6 | 1,224 | Normal |
| #7 | 1,322 | Normal |
| #8 | 1,417 | Normal |
| #9 | 1,372 | Normal |
| #10 | 1,443 | Normal |
| #11 | 1,497 | Normal |
| #12 | 1,401 | Normal |
| #13 | 1,416 | Normal |
| #14 | 1,414 | Normal |
| #15 | 1,399 | Normal |
| #16 | 1,246 | Normal |
| #17 | 1,223 | Normal |
| #18 | 2,287 | Anomaly |
| #19 | 1,065 | Normal |
| #20 | 1,073 | Normal |
| #21 | 1,098 | Normal |
| #22 | 1,143 | Normal |
| #23 | 1,077 | Normal |
| #24 | 1,157 | Normal |
| #25 | 1,248 | Normal |
| #26 | 1,216 | Normal |
| #27 | 1,313 | Normal |
| #28 | 2,666 | Anomaly |
| #29 | 1,482 | Normal |
| #30 | 1,414 | Normal |
| #31 | 1,458 | Normal |
| #32 | 1,482 | Normal |
Signal feed
Ranked by revenue at risk
- CriticalCheckout conversion −18.4%EU region · 6 min ago
- DegradedFeature drift on churn_v4PSI 0.27 · 24 min ago
- WarningLate-arriving Shopify rows1,204 rows · 1 h ago
- HealthyNightly reconciliation passed412 checks · 3 h ago
Connected to the stack you already run
Dashboards built the way analysts actually read
Colourblind-safe palettes, one axis per chart, hairline grids and a table view behind every figure. These are live components from real DataSwain workspaces — hover anything.
Know which lever actually moved the number
Marketing, finance and ops stop arguing about whose spreadsheet is right. One modelled revenue layer, one definition per metric, and a forecast that updates every night against what actually landed.
- Attribution unified across paid, organic, retail and marketplace
- Nightly forecasts benchmarked against booked actuals
- Cohort retention your CFO will sign off on
ARR
$38.2M
+22.4%vs last 30d
Gross margin
71.4%
+2.8%vs last 30d
CAC payback
9.2 mo
-11.5%vs last 30d
Net revenue retention
118%
+6%vs last 30d
Observed revenue joined to the modelled forecast
Daily, next 14 days — one axis, interval widens with the horizon
- Observed
- Forecast
- 80% interval
| Period | Net revenue observed and forecast | Basis | 80% interval |
|---|---|---|---|
| Aug 25 | $344,505 | Observed | — |
| Aug 26 | $370,779 | Observed | — |
| Aug 27 | $368,361 | Observed | — |
| Aug 28 | $371,736 | Observed | — |
| Aug 29 | $385,459 | Observed | — |
| Aug 30 | $396,150 | Observed | — |
| Aug 31 | $391,360 | Observed | — |
| Sep 1 | $392,081 | Observed | — |
| Sep 2 | $399,207 | Observed | — |
| Sep 3 | $397,989 | Observed | — |
| Sep 4 | $383,508 | Observed | — |
| Sep 5 | $401,943 | Observed | — |
| Sep 6 | $398,943 | Observed | — |
| Sep 7 | $410,684 | Observed | — |
| Sep 8 | $419,474 | Observed | — |
| Sep 9 | $410,192 | Observed | — |
| Sep 10 | $419,611 | Forecast | $407,023 – $432,199 |
| Sep 11 | $421,967 | Forecast | $404,455 – $439,479 |
| Sep 12 | $418,613 | Forecast | $396,427 – $440,799 |
| Sep 13 | $415,009 | Forecast | $388,241 – $441,777 |
| Sep 14 | $409,600 | Forecast | $378,470 – $440,730 |
| Sep 15 | $413,127 | Forecast | $376,978 – $449,276 |
| Sep 16 | $419,987 | Forecast | $378,408 – $461,566 |
| Sep 17 | $431,443 | Forecast | $383,769 – $479,117 |
| Sep 18 | $434,590 | Forecast | $381,570 – $487,610 |
| Sep 19 | $430,339 | Forecast | $372,889 – $487,789 |
| Sep 20 | $427,089 | Forecast | $365,161 – $489,017 |
| Sep 21 | $420,555 | Forecast | $354,738 – $486,372 |
| Sep 22 | $426,478 | Forecast | $354,830 – $498,126 |
| Sep 23 | $435,438 | Forecast | $357,277 – $513,599 |
Predicted outcomes
Ranked by modelled likelihood, next 14 days
- Quarter revenue target metrevenue_v7 · 14-day horizon87%
- EU checkout churn spikedriver: latency p95 · 7 days64%
- Paid search CAC over capdriver: auction density · 10 days41%
- Warehouse spend overrundriver: ad-hoc query volume23%
Where the modelled lift comes from
Share of the forecast delta, by driver
| Category | Contribution to the forecast delta by driver |
|---|---|
| Retention | 31 |
| Paid mix | 24 |
| Pricing | 19 |
| New SKUs | 15 |
| Seasonality | 11 |
Revenue by channel
One hue per channel, last 30 days
- Paid search$3.4M
- Organic$2.9M
- Email$1.9M
- Marketplace$1.6M
- Retail$1.2M
- Affiliate$690K
| Item | Revenue by acquisition channel |
|---|---|
| Paid search | $3,420,000 |
| Organic | $2,880,000 |
| $1,940,000 | |
| Marketplace | $1,610,000 |
| Retail | $1,180,000 |
| Affiliate | $690,000 |
Warehouse rows by source
Share of the modelled layer
| Segment | Value | Share |
|---|---|---|
| Snowflake | 4,200 | 42% |
| BigQuery | 2,600 | 26% |
| Postgres | 1,800 | 18% |
| S3 / Iceberg | 1,400 | 14% |
Cohort retention
Share of each signup cohort still active, by month
| Cohort | M0 | M1 | M2 | M3 | M4 | M5 |
|---|---|---|---|---|---|---|
| Apr | 100% | 68% | 54% | 46% | 41% | 38% |
| May | 100% | 71% | 58% | 49% | 44% | — |
| Jun | 100% | 74% | 62% | 55% | — | — |
| Jul | 100% | 77% | 66% | — | — | — |
| Aug | 100% | 81% | — | — | — | — |
Comprehensive Data & AI Solutions
From cloud modernization to GenAI-powered insights, we deliver end-to-end data solutions that transform your business capabilities.
Cloud Data Platform
Modernize your data infrastructure with scalable, AI-ready lakehouse architecture built on AWS.
Data Engineering
Build reliable data pipelines that transform raw data into trusted, decision-ready insights.
Predictive Analytics
Move from hindsight to foresight with ML-powered forecasting and predictive models.
AI-Powered Insights
Enable natural language interaction with your data using secure GenAI solutions.
Industry Solutions
Domain-focused data and AI solutions tailored to your industry's unique challenges.
Data Governance
Ensure secure, governed, and compliant data platforms without slowing innovation.
A single orbit where every system snaps into the same chromatic flow
Power finance, marketing, and ops with connectors that inherit the violet → magenta → teal spectrum so every experience stays cohesive. Automations deploy in minutes with governance baked in.
Compose branching automations with guard-rails that keep data residency intact.
Scoped tokens, field-level encryption, and audit-grade observability by default.
AWS
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Architecture
Secure
Security
Rapid
Deployment
Dataswain Engagement Model
Turn data into predictive, AI-driven business advantage, securely and at scale
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Assess current state, define goals, and create roadmap
Design & Build
Architect solutions and develop core capabilities
Deploy & Optimize
Launch solutions and tune for performance
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Transfer knowledge and expand capabilities
Why Choose Dataswain?
We combine deep technical expertise with industry knowledge to deliver data solutions that drive real business outcomes.
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Built on proven cloud infrastructure for reliability and scale
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GenAI and ML capabilities built into every solution
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Built-in governance and compliance controls
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