Michael Chen
- m.chen@helixmfg.com
- Phone
- (415) 555‑0142
- Company
- Helix Manufacturing
Under the hood
48 hours sounds impossible. Here’s the engine behind it.
Connecting systems, untangling data, and reverse-engineering your real numbers is normally a year-long data project. Synopsis does all of it — and the customer does none of the work.
Ingest
Store
Model
Link
Understand
Ingest
Connect anything.
Connect anything.
Automatically.
APIs, databases, and files — Synopsis ingests them all. 500+ sources work out of the box, and when something's custom, AI reads the API's own docs and builds the connector for you. No integration engineer required.
Any API
Any database
Any file
It's all automatic — you do none of it.
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of 12 connected
STORE
Your data, organized the moment it lands.
Every change in every system streams in as an event — and Synopsis automatically organizes it by entity at massive throughput. No pipelines to build, no schemas to babysit. The chaos of raw data becomes a clean, structured picture of your business, on its own.
Built automatically as your data flows in.
sort by entity
Account
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Contact
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Invoice
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A data engineering team’s work — done for you.
No new hires, no data expertise on your side. Synopsis builds the model and keeps it current — automatically, forever.
It profiles, cleans, and reshapes your raw history into a modeled data lake — and keeps it current as your data changes. No SQL, no migrations, nothing to maintain.
Automatic column profiling
Cleaning & normalization
Prebuilt transformers
Custom SQL & Python
Instant rebuilds
Synopsis applies:
| id | full_name | ssn | zip |
|---|
All automatic. Synopsis writes and applies the modeling, the rebuilds, and the versioning. You do none of it.
Entity resolution
One customer. Every system. Automatically linked.
“Michael” in your CRM and “Mike” in your ERP are the same person — Synopsis figures that out, even when there’s no shared ID. Confident matches link automatically; the in-between cases that used to need a human are reviewed by AI. So you can finally ask questions that span every system.
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confidence
Auto‑merged
Mike Chen
- m.chen@helixmfg.com
- Phone
- +1 415‑555‑0142
- Company
- Helix Mfg.
Above the bar → auto‑linked
In between → AI reviews it
It’s all automatic — you do none of it.
Not just an answer — the right answer.
Most tools can produce a number. Synopsis reverse-engineers how your team actually calculates it — from your own budgets, board decks, and operating reports — until it matches your authoritative figures. When a definition is genuinely ambiguous, it asks. Then every future answer is the correct one.
Test cases from your docs
Reverse-engineered formulas
Clarifying questions
MetricPlanActual
Net Revenue Retention110%112%
Gross Margin73%74%
Active Customers1,8001,840
Definitions tab → "active = paid,
non-trial"
ACME OPERATIONS · CONFIDENTIAL
Monthly Operating Report
Finance & Revenue · Q3 FY26
Topline performance held through the quarter. Expansion within the installed base offset modest logo churn, and net revenue retention finished at 112%, ahead of plan. Gross margin was stable at a blended 74% as cloud costs normalized. We closed the period with an active customer base of 1,840, though the trial cohort remains a definitional question for the board.
Net Revenue Retention112%
Gross Margin74%
Active Customers1,840
Methodology and segment detail follow in the appendix. Figures are reconciled to the board reporting package and the FY26 operating budget.
TEST CASE
expected 112%
Net Revenue Retention
(start_arr + expansion − contraction − churn) / start_arr
TEST CASE
expected 74%
Gross Margin
(revenue − cogs) / revenue
TEST CASE
expected 1,840
Active Customers
count(distinct customer_id) where status = 'active'
raw tables
arr · expansion · churn SQL probe
iterating… verified
arr · expansion · churn SQL probe
iterating… verified
an answer: 108%
the correct answer: 112%
Does “active customer” include trials?
Reverse-engineered automatically — you do none of it.
Teams already running on Synopsis.
Real companies, real systems, real answers.
Case study
Becoming AI-Powered: A Bet on the System.
How Leap connected every system it runs and let Synopsis build the data foundation underneath it — automatically.
Read the case study
Case study
Building the One Knox Way.
How One Knox brought its systems together into a single, queryable foundation — the work done for them, not by them.
Read the case study
Case study
How Relay Found $100K in Lost Revenue in Its First Weeks.
How Relay chose Synopsis over standing up a data lake — and recovered six figures of leaked revenue within weeks of going live.
Read the case studyThe AI space is full of snake oil right now. Synopsis is the exception — they told us exactly what it would do, and it did exactly that.
See it in action
See it on your own data.
Most demos take about 30 minutes. Bring a question you've been waiting months to answer.
