Now streaming validation at scale

Every transaction has a story.
We verify the truth.

Stratos checks every order, product, and payment line by line, resolves phone and date formats by country, and turns the result into AI-generated insights your team can act on immediately.

Start validatingView a sample report
Streamingingestion engine
6-stagevalidation pipeline
Groq-powered insights
1.2Mrecords processed
100.00%accuracy
190+country rules
32active jobs
The problem

Transaction data breaks in ways spreadsheets don't show you.

It looks fine until finance reconciles it, support escalates it, or a regulator asks for it.

01

Phone numbers are formatted differently in every export, and most validators only know one country.

02

Payment fields drift silently between gateways — currency, status, and ID formats all shift without warning.

03

Date formats mix inside the same file. One ambiguous row can break an entire reconciliation run.

Built for teams that can't afford to guess
Fintech Operations
Retail & Commerce
Logistics
Healthcare Billing
Marketplaces
The pipeline

Six stages stand between a messy export and a number you can report on.

Every file moves through the same ordered path — nothing skipped, nothing assumed.

01

Ingest

Drop in a CSV or Excel file, a few rows or a few million. Stratos streams it chunk by chunk — nothing loads fully into memory.

02

Validate

Every order, product, payment, phone number, and timestamp is checked against rules written for real-world messiness, not clean test data.

03

Clean

Malformed rows are repaired where the fix is unambiguous, and set aside where it isn't. You see exactly what changed and why, row by row.

04

Enrich

Country codes are resolved, currencies normalized, and duplicate orders linked together — restoring context the source file never had.

05

Analyze

Groq reviews the dataset as a whole and writes a plain-language quality report — patterns and root causes, not just a list of broken rows.

06

Trust

A clean export, an error report, and chunked files land wherever your downstream systems expect them. Ready to reconcile, not just review.

Architecture

POWERING THE VALIDATION ENGINE

Every uploaded dataset flows through a streaming validation pipeline before being transformed into clean data, downloadable reports, and AI-powered insights.

190+
Validation Rules
40+
Countries Supported
∞
Streaming Processing
LLM
AI Insight Generation
Auto
Automatic Chunking
BG
Async Background Jobs
LitestarAPI LayermsgspecSerializationPolarsProcessing EnginePanderaSchema ValidationPostgreSQLStorageRedisQueueGroq APIAI Intelligence
Pipeline Flow
Upload
CSV or XLSX streamed chunk by chunk
→
Validate
190+ rules checked per record
→
Process
Polars transforms and normalises data
→
Store
Results persisted to PostgreSQL
→
Analyze
Groq generates quality insights
→
Export
Clean CSV, error report, chunks ready
Configuration, not hardcoding

Validation rules you can see — and change.

Phone formats and date parsing are configuration, not code. Add a country or a format without shipping a release.

country-rules.yaml
🇮🇳 India
10 digits
🇸🇬 Singapore
8 digits
🇺🇸 USA
10 digits
🇩🇪 Germany
11 digits
date-formats.yaml
ISO
YYYY-MM-DD
EU
DD/MM/YYYY
US
MM/DD/YYYY
Germany
DD.MM.YYYY
Singapore
DD-MM-YYYY
Unix epoch
seconds
AI-generated insights

Not an error list. A reason.

Groq reads the whole batch the way a senior analyst would — looking for what's connected, not just what's broken.

①

Root-cause grouping. Hundreds of failed rows collapse into a handful of underlying causes.

②

Plain-language summaries. Written for the person who has to explain this batch to finance, not just the engineer who built the pipeline.

③

Trend awareness. Flags when this batch's error pattern is new, not just whether it failed.

data-quality-report — batch #4471
92
Dataset quality score
92 / 100 — above your 90 threshold
Finding — Malformed phone numbers from the DE region rose 12% in this batch, concentrated in orders placed after 18:00 UTC. Pattern matches a checkout form regression, not random noise.
Phone
62%
Payment
18%
Date/Time
12%
Product
8%
AI recommendations
✓Review Singapore phone formats — 8-digit rule may be misapplied to landlines.
✓Check the payment export configuration for the DE checkout flow.
✓Investigate payment anomalies clustered after 18:00 UTC.
0.00%
validation accuracy maintained across every batch processed last quarter
2.1M rows/minsustained streaming throughput on a single worker pool
<400msaverage validation latency per batch, end to end
40M+transactions validated since deployment

Every transaction,
verified.

Bring your messiest export. Leave with data your finance team actually trusts.

Start validating freeTalk to the team