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Data Standardization Agent — clean, normalized data
Data & Analytics Agent

Data Standardization — Clean, Mapped Data

Cleans, normalizes, and maps disparate data to common schemas and standards — inside your own environment.

Trustworthy Data, Automatically

Every analytics and AI initiative stalls on the same problem: data that's inconsistent, siloed, and hard to trust. The Data Standardization Agent fixes it at the source — cleansing, mapping, and validating continuously — so the data feeding your warehouse, dashboards, and agents is clean.

Consistent

Every source

One trusted schema across all inputs

Fewer errors

Downstream

Bad records caught before they spread

Any source

DB · file · API

Ingests from wherever your data lives

Private

By default

Data is processed in your environment

Data Standardization Architecture

The Platform, Specialized for Data Quality

The Data Standardization Agent runs on the same base Vervelo Agents Platform architecture as every other agent — here, a durable runtime powers batch pipelines, a streaming runtime handles live ingest and mapping, and the connected tools are the source, warehouse, and schema-registry systems standardization depends on.

Data Standardization Agent Clean, normalized, mapped data — on the Vervelo Agents Platform DURABLE EXECUTION · BATCH PIPELINES SYNC EXECUTION · STREAMING INGEST Source Systems / Files FastAPI Service Standardization Agent Mapping Agent Observability Source Data DB / Files / API Warehouse / Lake (MCP) Schema Registry & Standards Mapping Store (Agents DB) Quality Reports & Logs Database Agent Definition Agent State Dataset Memory Job Sessions Mapping Tools Warehouse MCP Schema Vectors Prompt Development Flow ITERATE FEEDBACK LOOP Define Task & Success Criteria Target schema, quality rules Draft Structure & Prompt Mapping logic, transforms Manual Testing Sample records & edge cases Automated Evaluation Data-quality eval suite Refine & Iterate Fix mismatches, bad maps Deploy & Monitor Track quality & coverage

Context Engineering

Engineered Context, Every Turn

Reliable agents aren't a single clever prompt — they're the product of context engineering: assembling exactly the right information into the model's context window on every turn. It's the discipline we build every Vervelo agent around. Here's what the Data Standardization Agent works from on each turn, and how we engineer it.

Data Standardization Agent context window

Assembled fresh on every turn

System Instructions

The standardization persona and rules — the target schema and standards, quality thresholds, and never to silently drop or guess at data.

Persona & roleBehavioral rulesOutput format

Tool Definitions

Ingest, transform, warehouse-write, and validation tools with strict schemas so mappings run safely and repeatably.

Name & descriptionI/O schemaUsage examples

Memory & User State

Dataset context — source quirks, prior mappings, and standing rules the team has approved over time.

PreferencesPast decisionsStanding instructions

Conversation History

The job's steps and any analyst guidance so far, so mappings stay consistent across a run.

User turnsAssistant turnsTool-call traces

Retrieved Knowledge

Schema vectors — target schemas, standards (FHIR / HL7 / industry), and prior mapping decisions — retrieved to map correctly.

Vector search hitsKeyword matchesDoc snippets

Environment Results

Profiling stats, transform results, and validation errors — surfaced so bad records are caught, not published.

API responsesFunction returnsErrors & status

Capabilities

From Messy to Trusted

Cleansing & De-duplication

Fixes formatting, fills gaps, and removes duplicates so records are consistent and reliable.

Schema Mapping

Maps disparate source fields to your common target schema, learning from prior mappings.

Standards Alignment

Normalizes data to industry standards like FHIR, HL7, and your own canonical models.

Validation & QA

Runs quality checks on every batch and quarantines records that fail your rules.

Continuous Pipelines

Runs as scheduled batches or streaming ingest so standardized data stays current.

Human Review

Surfaces low-confidence mappings and exceptions for a data steward to approve.

How it works

From Raw Source to Clean Table

01

Ingest

Pulls data from databases, files, and APIs — batch or streaming.

02

Profile

Analyzes structure and quality to understand each source's quirks.

03

Map

Cleanses and maps fields to your target schema and standards.

04

Validate

Runs quality checks and quarantines anything that fails the rules.

05

Publish

Writes clean, standardized data to your warehouse or lake, with a quality report.

Powered by the Vervelo Agents Platform

Open Source. On Your Infrastructure.

The Data Standardization Agent is built on our open-source platform — deployable in your cloud, on-prem, or air-gapped — so your data never leaves your environment to be cleaned or mapped.

Explore the Platform →

Secure, Standards-Aligned Data Handling

The agent is built with audit logging, access controls, and safe data handling aligned to standards like SOC 2, GDPR, and HL7 FHIR for healthcare data — and because you self-host, sensitive data stays inside your environment.

SOC 2 GDPR HL7 FHIR
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Vervelo is a digital-health software partner blending deep clinical insight with world-class engineering to build tailored, secure, interoperable healthcare platforms.

Benefits of custom software solutions
  • Software delivered ownership benefit

    You fully own IT consulting and software delivered

  • Highly personalized solution benefit

    You get a highly personalized solution

  • Integration capability benefit

    Customize and integrate seamlessly

  • Scalability benefit

    On-demand scalability is always possible