5 AI agents working in sequence

Messy CSV in.
Clean data out.

Upload your messy spreadsheet. Our AI agents map columns, normalize formats, and validate every row — in under 60 seconds. No SDK. No integration. Just clean data.

dataweave pipeline

$ POST /api/upload contacts.csv

▸ Ingestion Agent: parsed 1,247 rows, 15 columns

▸ Pattern Agent: matched 10 columns (FREE)

▸ Schema Agent: mapped 5 unknowns via Claude ($0.01)

▸ Transform Agent: normalized dates, emails, phones

▸ Validation Agent: quality score 89.5%

Pipeline complete — clean_contacts.csv ready

0
AI Agents
<0s
Processing Time
0%
Quality Score
0¢
Per File Cost

Workflow

Three steps. Zero complexity.

STEP 01

Upload

Drag and drop your CSV, Excel, or JSON file. Select your target schema (HubSpot, Salesforce, or custom).

STEP 02

Review

Our AI maps every column automatically. Review the proposals — approve, reject, or correct with one click.

STEP 03

Export

Download your clean, schema-compliant data as CSV or JSON. Ready to import into your target system.

Architecture

Five agents. One pipeline.

Each agent handles a single responsibility. Three are fully deterministic (no AI cost). Only the Schema Agent calls an LLM — and only for columns it hasn't seen before.

01
No LLM

Ingestion Agent

Parses CSV, Excel, JSON, and TSV. Detects encoding, sniffs delimiters, infers column types, normalizes null values.

02
No LLM

Pattern Agent

Checks every column against a database of known mappings. Gets smarter with every correction. 67% hit rate and climbing.

03
LLM for unknowns

Schema Agent

Sends unknown columns to Claude in a single batched call. Caches results. Blends LLM confidence with heuristic boosts.

04
No LLM

Transform Agent

Renames columns, casts types, parses 15+ date formats to ISO 8601, normalizes emails and phone numbers.

05
No LLM

Validation Agent

Checks required fields, type conformance, format validation, duplicates, and statistical anomalies. Produces a quality score.

3 of 5 agents
cost $0.00

Only unknown columns trigger an LLM call. As patterns learn, AI costs approach zero.

Transformation

See the difference.

messy_contacts.csv

Col A: Cust Email

Col B: Signup Date

Col C: Org

Col D: State/Province

Col E: Personal Website

⚠ Mixed date formats (MM/DD, DD-MM, "Jan 15")

⚠ Phones: +44-20-555, (555)010, 5550104

⚠ Missing required fields on 3 rows

clean_contacts.csv

email: john.doe@acme.com

created_at: 2024-01-15

company: Acme Corporation

state: CA

website: https://johndoe.dev

✓ All dates ISO 8601

✓ Phones normalized to +1XXXXXXXXXX

✓ Quality score: 89.5%

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