Turn survey data processing into a reusable, automated pipeline
Purify Intelligence connects to your survey data, applies governed and repeatable transformations, and delivers analysis-ready data wherever your team needs it. Every change is traceable, every pipeline is reusable, and every new wave is easier to deliver.
The problem
Survey data processing should not start again with every project
Too many research teams still depend on manual exports, one-off scripts, and knowledge held by a small number of people. That makes repeat studies slower, harder to check, and more expensive to change.
Repeated manual work
The same cleaning, recoding, and restructuring is rebuilt for each project or repeated by hand for every wave.
Fragile delivery
Processing logic is spread across files, scripts, and individual expertise, making quality assurance and handover difficult.
Data that disappears
Once the tables and presentation are delivered, valuable project data is archived instead of becoming a reusable asset.
Connect
Bring in survey data without losing the source
Raw data is preserved exactly as received before any cleaning, recoding, or reshaping, so downstream outputs remain traceable.
Upload survey files
Bring in survey data files, including SPSS .sav files, without building a new import process for every project.
Connect to collection platforms
Pull data directly from supported survey platforms, reducing manual export steps and making repeat delivery easier to automate.
Preserve the original
Keep an unchanged source layer so your team can audit processed data back to what was originally received.
Transform
Turn raw responses into consistent, analysis-ready data
Use reusable recipes for common survey-processing tasks, with the flexibility to handle the specialist logic that complex projects demand.
Reusable transformations
Apply repeatable processing patterns for cleaning, recoding, reshaping, and creating derived variables.
Advanced custom logic
Use custom PostgreSQL statements when a project needs more complex logic, supported by a cookbook of common survey tasks.
Respondent attributes
Turn selected answers into reusable respondent-level attributes for filtering, analysis, and downstream modelling.
Survey weighting
Create weighting variables using iterative RIM weighting, with repeatable specifications for future waves.
Loop handling
Unpack looped question blocks into clean structures that can be queried and analysed consistently.
Reference data
Bring classifications, mappings, and other reference data into the project and use them throughout processing.
Standardise
One consistent structure for every survey
However a survey was fielded, we convert it into the same consistent data model. That means queries, transformations, and downstream integrations can be reused across projects instead of being rebuilt around each source format.
For technical teams, the model uses four linked core tables: fact responses, codebook, respondents, and sources.
Automate
Set the pipeline once, then run it again
Schedule repeat workflows to collect new responses, apply the agreed processing, and deliver updated outputs with less manual intervention.
Govern
Know what changed, when it changed, and how to recover
Processing stays visible and controlled, so changes do not disappear inside an undocumented script or spreadsheet.
Source lineage
Trace processed data back to the original source and understand how it moved through the pipeline.
Transformation history
See which transformations were applied and maintain a shared record of the processing workflow.
Version recovery
Return to an earlier project version when a processing change needs to be undone or reconsidered.
Responsible AI
AI where judgement helps. Deterministic logic where it matters.
Cleaning rules, recodes, and calculations should be predictable, auditable, and repeatable. We use deterministic transformations for those jobs.
When a task requires interpretation, such as sentiment classification, language detection, translation, or understanding open text, AI can be introduced as a governed step in the same pipeline.
The right tool for the job, not AI for AI's sake.
AI-assisted transformations
Apply AI without turning every project into a prompt-engineering exercise
Use prepared recipes for common text tasks or create new variables from existing responses while keeping the work inside the governed processing pipeline.
Ready-made AI recipes
Use reusable recipes for tasks such as sentiment classification, language identification, label translation, and text cleaning.
Create derived variables
Generate structured variables from open text, such as brand-mention flags, classifications, or cleaned verbatims.
Choose your AI provider
Connect your own OpenAI or AWS Bedrock account so model choice, usage, and cost remain under your control.
Deliver
Send finished data where your team and clients need it
Purify Intelligence fits into your existing research and analytics stack rather than trapping processed data inside another platform.
Export to SPSS
Deliver response data and metadata as a ready-to-use SPSS .sav file for familiar research workflows.
Deliver modern data files
Export one or more tables as Parquet or Excel files for storage, downstream processing, or business intelligence.
Use your own storage
Deliver data directly to your own S3 bucket using restricted, customer-controlled access, helping you avoid platform lock-in.
Backup & restore projects
Import or export an entire project for backup, or to restore it later.
MCP (in beta)
Work with Purify Intelligence from the AI assistant you already use
Our Model Context Protocol (MCP) server is in beta. It allows compatible AI assistants to turn plain-language instructions into governed transformations.
Use a compatible assistant
Connect from Claude or another MCP-compatible environment without moving the underlying data workflow into a separate tool.
Describe the change
Explain the transformation in plain language and let the assistant help translate it into an executable processing step.
Keep it governed
Run assisted transformations through the same controlled and auditable pipeline as other project processing.
Designed to fit your research stack
Extend the platform around the way your organisation works
Survey programmes differ. Purify Intelligence provides a consistent foundation while allowing specialist integrations and proprietary processing logic to be added where needed.
Additional data sources
Connect other survey and research platforms when your workflow extends beyond the integrations already available.
Specialist transformations
Add transformation logic for the classifications, calculations, and delivery rules that make your projects distinctive.
Protect proprietary methods
Keep custom business logic and proprietary research methods private to your organisation.
Why Purify Intelligence
Deliver repeat studies faster and with greater confidence
Built specifically for complex survey data, Purify Intelligence gives research teams a reliable processing foundation without forcing them to replace the tools they already use.
Survey-native
Designed around respondents, questions, codebooks, loops, weighting, derived variables, and the realities of research delivery.
Reduce repetitive processing
Create transformation logic once and reuse it across waves, markets, and future projects instead of rebuilding the same workflow.
Make quality visible
Preserve the original source and review the transformation history and current output without reconstructing what happened from scattered files.
Remove key-person dependency
Keep processing logic in a consistent, documented workflow that the wider team can understand and operate.
Open at both ends
Connect to existing survey platforms and deliver analysis-ready outputs into the statistical, storage, and business intelligence tools your team already uses.
Build value over time
Retain structured survey data that can be queried, combined, and reused after the original project has ended.
See what your survey workflow could become
Bring a sample survey or talk us through a repeat project. We will show you how Purify Intelligence can connect, transform, govern, and deliver the data.