For Humanitarian & Field Research

Field research that stays usable after collection.

Plan multilingual assessments, collect structured or voice responses when appropriate, and move field records into analysis with consent, language, and source context intact.

Start a fieldwork trial
95+Study languages

Prepare instruments, consent text, collection links, and response modes in the languages the context needs

3 collection modesDuring collection

Structured forms, chat-style flows, or voice response, whichever fits the setting

Reviewable sourcesAfter collection

Transcripts, follow-ups, metadata, and imported field datasets stay available for analysis

How it works

From field setup to reviewable assessment

01Step 1

Rapid design

Use assessment templates or build custom instruments for the field context.

02Step 2

Deploy with context

Prepare links, language settings, consent text, and collection modes before fieldwork begins.

03Step 3

Collect via voice or form

Use voice response or structured forms when appropriate, keeping transcripts and response records available for review.

04Step 4

Review incoming evidence

Review responses as they arrive, flag quality issues, and move coded records into briefs or reports when the assessment team is ready.

app.heurista.ai · study · setup
Heurista project setup wizard for choosing collection and analysis goals
app.heurista.ai · study · distribution
Heurista distribution screen with multilingual survey links
app.heurista.ai · study · response matrix
Heurista response matrix for reviewing field data and quality flags
app.heurista.ai · study · report package
Heurista report package workspace with draft finding, evidence links, and review outputs

Relevant tools

Tools for multilingual field evidence

Voice Response Collection

Collect spoken responses when that fits the setting, with transcripts available for review.

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AI Conversational Interviews

Use chat-style interviews with reviewable transcripts and configured follow-up prompts.

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Field Data Import

Bring structured field datasets into Heurista for analysis and reporting.

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Field Collection Planning

Set up language, consent, links, and collection modes before data collection starts.

Plan collection

Rapid Assessment Templates

Pre-built templates for needs assessments, PDMs, KAP surveys, and other common humanitarian instruments.

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Multilingual Outputs

Field summaries and findings drafts that carry the original-language responses through to translation, with source citations preserved.

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Reviewable AI support

Where AI fits in assessment review

Heurista uses AI where it can reduce research labor, but the useful unit is still a reviewable suggestion, query answer, or draft tied back to the study record.

  1. 01

    Voice and multilingual coding

    Hue can suggest codes for interview transcripts and flag uncertain assignments. Reviewers verify before findings move forward.

  2. 02

    Live field queries

    Ask plain-language questions of incoming data. Answers map back to respondents, locations, and timestamps where those fields are available.

  3. 03

    Field-ready summaries

    Assessment briefs and rapid summaries keep source responses cited so the line from finding to evidence stays clear.

Trust

Controls for field research data

Encryption in transit

TLS encryption in transit, with clear controls for account and study access.

AI data protection

Research data is handled under commercial API terms and is not used to train public AI models.

Full audit trails

Every action logged with timestamps, user identity, and change history.

Role-based access control

Granular permissions for team members, reviewers, and external stakeholders.

Security documentation

Privacy Policy, DPA, and data subject rights documentation are available for procurement review.

Research consent support

Consent screens, participant notices, and study-level controls support responsible fieldwork.

Next step

Your next assessment starts here

Field collection, multilingual response records, and analysis workflows for rapid assessment cycles.

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Human review  ·  No training on your data  ·  Source-linked findings