- Candidate A · Atlas CRMPending
- Candidate B · NorthstarPending
- Candidate C · RelayPending
Describe what the solution must do. Weight the requirements that matter. Market Dog . AI helps shortlist candidates, score them on one shared grid, and keep the evidence behind the recommendation.
One study · Weighted requirements · Traceable evidence · Human decision
From research to decision
Each study keeps the need, candidate list, weighted scoring grid, and supporting evidence in one decision trail.

See every study, its stage, candidate count, and requirements count from one workspace. Filter, sort, and return to the work when the decision moves.

Every candidate is assessed against the same weighted requirements. Rationale, citations, research confidence, and manual edits stay visible.

Move from the comparison matrix to a ranked shortlist, then record the selected solution and the accountable human rationale.
Study workflow
Each stage narrows the decision while keeping the assumptions, weights, candidates, scores, and evidence connected.
Describe the functional goal, context, countries, constraints, decision owner, and what is explicitly out of scope.
Build business, IT, and purchasing criteria. Mark MUST, SHOULD, and COULD priorities, including disqualifying requirements.
Add solutions yourself or use AI suggestions, verify official websites, and keep only the candidates worth analysing.
Review AI scores and evidence, adjust any cell, compare the ranking, and record the final human decision with its rationale.
Decisions this fits
Use the same evidence-backed workflow whether you are exploring a new category or challenging an incumbent.
Translate a business need into weighted requirements, discover plausible candidates, and compare functional fit before committing.
Set the incumbent as the baseline, state why it may be replaced, and compare alternatives against the same decision criteria.
Give stakeholders a consolidated matrix, documented scores, candidate profiles, and exports they can review outside the app.
Keep in-progress and ready studies, plus earlier saved versions, organised so the next decision starts from a clear record.
Questions, answered
The essentials about the method, the AI, and the resulting evidence.
An AI-assisted market-study workspace that turns a functional need into weighted requirements, a candidate shortlist, an evidence-backed comparison, and a recorded human decision.
A spreadsheet can hold scores, but it does not keep the need, weighting method, candidate research, citations, confidence, ranking, and final rationale connected. Market Dog . AI keeps that decision trail in one study.
It can refine the need, propose criteria, suggest candidates, and score solutions against the grid with rationale and citations. Suggestions remain reviewable, scores stay editable, and the final decision remains human.
Export the study as Word, PowerPoint, PDF, Excel, Markdown, or JSON. The report includes the shortlist, matrix, evidence, candidate profiles, and recorded decision available at export time.
Yes. AI is configured per workspace, with a platform option or your own provider key. Stored keys are encrypted, and study access remains scoped to workspace membership.
Create a study, describe the need and target countries, then review the weighted requirements before adding candidates. You control every stage before analysis begins.