Find out whereyou miss opportunities.you lose money.you lose money.

accounts billed below cost

282828

of volume left out by one key table

76%76%76%

audits in parallel

171717

The result

The review exposed what nobody was watching: 28 accounts billed below the vendor's cost, and a daily table feeding every money figure while leaving out 76% of the real volume. The findings were fixed in batches, and each fix was checked against the invoice before it was closed.

The problem

The numbers lived spread across six systems, and every report to the committee was put together by hand. Nobody could say where a figure came from, and pricing and billing errors surfaced weeks later, on the customer's invoice.

The solution

An audit standard: every number on screen can be traced to the table and the line of code that produced it, and the platform checks itself against the vendor's invoices, with an automatic alert when it drifts more than 1%. Under that standard, 17 audits ran in parallel, one per feature.

Stack

Next.js · BigQuery · AWS Aurora · Google Cloud Run · Slack

accounts with an auditable report · 136 active

347347347

data traps controlled

464646

in query costs

$0$0$0

The result

347 accounts indexed, 136 active plus the full history, each with its auditable report available at any time instead of a PDF put together on request. The sales team asks and gets the number with its source table and date next to it, so it can be defended in front of the client; when the evidence isn't enough, the system answers “not available” instead of inventing one. The portal serves versions already calculated, without querying the analytics database, and the folder runs on the user's computer over files already downloaded: in both cases a query costs $0.

The problem

Every number about an account depended on someone putting it together by hand: it arrived late, for a few, and nobody could say what table it came from or what day it was from. And nobody on the sales team writes SQL.

The solution

Two pieces on the same engine. A portal where each account comes in through its own link and sees only its report, recalculated every day and frozen into versions that can't be altered. And a folder each rep installs with a single command, with an agent that turns a plain-language question into the query. The hard part was getting the system to refuse to answer when the evidence isn't enough. First the 46 known data traps were documented and turned into permissions and tests the agent can't skip.

Stack

Next.js · BigQuery · DuckDB · Parquet · Python · Cloud Run

security checks

545545545

tests passing

4,8144,8144,814

weeks of development

333

The result

From zero to deployed on production infrastructure in three weeks. The security audit ran 545 checks across 186 routes: no anonymous request reached data, and no account read or changed another account's information. 4,814 automated tests green.

The problem

The company sends printed letters and postcards on behalf of its clients: real money moving, and pieces that can't be undone once they're printed. Two earlier attempts never became a product an operator, not an engineer, could use every day.

The solution

The complete app: the client uploads a list, picks the artwork, tops up a wallet with a card and launches the campaign; the system coordinates with the print vendor, tracks every piece through to delivery and attributes the sales results. Money is held in whole cents on an append-only ledger, so a charge can't be duplicated and a piece can't be printed twice.

Stack

Next.js · PostgreSQL · Stripe · Lob · Firebase

Deployed; pilot with real money still pending.