For Program Evaluators & M&E Teams

Evaluation work, from canvas to evidence-backed report.

Set up the evaluation canvas, choose the framework your assignment requires, map evidence to key questions, and keep report drafts connected to the source record.

Start an evaluation trial
OECD-DAC + customEvaluation setup

Use OECD-DAC when it fits, theory of change, or a custom framework, without forcing the assignment into one model

Source matrixEvidence review

Map documents, transcripts, responses, excerpts, and reviewer notes to each key evaluation question

Report packageOutputs for review

Draft findings, evidence matrices, quote banks, source indexes, and reviewer notes for handoff

How it works

From evaluation canvas to evidence-backed findings

01Step 1

Build the evaluation canvas

Set key evaluation questions, criteria, themes, indicators, and source requirements before analysis starts.

02Step 2

Bring sources into the matrix

Import or collect structured responses, documents, transcripts, and field records into a single evidence matrix, organized by key evaluation question.

03Step 3

Triangulate by question

Each key evaluation question gets its own row; triangulate survey, qualitative, and document evidence side by side, with every AI suggestion editable before it supports a finding.

04Step 4

Draft report sections

Prepare findings, evidence matrices, charts, and executive summaries with reviewer-visible links back to source material.

app.heurista.ai · demo · evaluation canvas
Heurista demo evaluation canvas with framework selection, key evaluation questions, indicators, and source requirements
app.heurista.ai · demo · source matrix
Heurista demo source matrix mapping evidence sources to key evaluation questions
app.heurista.ai · demo · evidence review
Heurista demo evidence review screen with candidate findings, evidence strength, and supporting sources
app.heurista.ai · demo · report review
Heurista demo report review screen with finding draft, evidence links, reviewer note, and export package

Relevant tools

Tools for evaluation design and review

Evaluation Canvas

Set up key questions, criteria, themes, indicators, and evidence requirements before analysis begins.

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Evidence Matrices

Each key evaluation question on its own row, answered by triangulating survey, qualitative, and document evidence, so every finding has a visible base.

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Response & Source Review

Review structured responses, uploaded documents, transcripts, quality flags, and source metadata before synthesis.

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Report Drafts

Draft evaluation report sections with evidence references that remain visible to reviewers.

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Framework-Aware Synthesis

Use OECD-DAC when it fits, or another framework pattern from the system, without forcing every evaluation into one lens.

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Audit Trail & Review

Keep coding, quality decisions, analysis steps, and report edits available for methodological review.

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Reviewable AI support

Where AI fits in the evaluation review process

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

    Framework-aware synthesis

    Hue organizes evidence around the evaluation canvas and framework you choose. Reviewers approve what moves into findings.

  2. 02

    Evaluation queries in plain language

    Ask questions across coded responses, transcripts, and uploaded documents. Answers show the responses, excerpts, or pages behind them where available.

  3. 03

    Report drafts for review

    Report drafts can be structured around your chosen framework — executive summary, methodology, results, and recommendations — with citations linked back to source.

Trust

Controls for evaluation 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

Findings that stand up to the funder’s reviewer

Move from field data to reviewed findings without rebuilding the chain between sources, codes, matrices, and report drafts.

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