PRISM vs Other Tools
Your research team is not underperforming.
The infrastructure around them is failing.
Prism vs
Research Repositories
Repository tools are libraries.
Prism is a research-to-decision engine
| Repository tools | Prism | |
|---|---|---|
|
Core promise |
“Organise your research.” Make it findable, searchable, and shareable within the research team. |
“Make research influence decisions.” Connect studies to business objectives, synthesise findings for executives, and track whether research drove action. |
|
Success metric |
Research findability. Can someone locate a past study? Is the repository well-tagged? |
Decisions influenced. How many business decisions were informed by research evidence? Can you prove it? |
|
Primary output |
A searchable archive of research data, transcripts, tags, and highlights. Researchers browse and extract what they need. |
Decision-ready briefs. AI-synthesised, researcher-verified summaries that executives can act on without navigating raw research data. |
|
Executive role |
Occasional viewer at best. The interface is designed for researchers. Executives rarely log in, and when they do, they see a researcher’s workspace. |
Primary consumer. Strategic briefs are designed for decision makers. Research reaches executives in the format they need, not the format researchers work in. |
|
Decision tracking |
None. The tool does not know whether research influenced any decision. There is no concept of a decision artefact or outcome verification. |
Core feature. Every study has a named decision owner. When research influences a decision, the link is documented. Researchers are notified when their work drives action. |
|
AI synthesis |
Some tools offer AI-assisted tagging or summaries within the repository. They’re designed to help researchers, not executives. |
Tiered AI synthesis designed for executive consumption. Quick summaries, study syntheses, cross-study analysis, and full strategic briefs. All verified by researchers before reaching stakeholder |
|
Impact measurement |
None. You cannot prove that research delivered value. When budget season comes, the research team has no data to justify their investment. |
Built in. Track which studies influenced which decisions. Measure research ROI in terms of decisions informed, not studies completed. Give the Head of Research data to defend the budget. |
|
Feedback loop |
None. Researchers produce work. It goes into the repository. They never learn whether it mattered. |
Researchers are notified when their work influences a decision. This changes the dynamic from “producing studies” to “informing strategy.” It is the single most requested feature from research teams. |
The pricing difference is structural, not just cheaper.
Per-seat pricing
10-person research team at £200 to £500 per user per month. Executives, product managers, and designers who should see research are excluded because each seat adds cost. The people who need research most are priced out of accessing it.
Activity Based Pricing
One price. Unlimited users. Your entire organisation can access research insights. 100 AI synthesis credits included. The pricing model reflects the goal: research should reach everyone who makes decisions, not just the team that produces it.
Prism vs
spreadsheets, slide decks, and shared documents
Most research teams track their work in spreadsheets, share findings through presentations, and store everything in Confluence pages or Google Drive folders. This is the most common "system" for research management and the most common reason research never reaches decisions.
| Spreadsheets & Documents | Prism | |
|---|---|---|
|
Research tracking |
A spreadsheet with columns for study name, status, owner, and dates. No connection between a study and the business question it serves. No link to the decision it should inform. When leadership asks what the research programme is delivering against strategy, someone builds a slide from the spreadsheet. |
Every study is commissioned against a business objective with a named decision owner. Research portfolio view shows coverage, gaps, and status by strategic priority. No manual reporting needed. |
|
How research reaches stakeholders |
A researcher presents findings in a meeting. Stakeholders receive a 40-page deck or a Confluence link. Engagement depends entirely on whether the right person was in that meeting. |
AI-synthesised briefs are delivered to named decision owners. Studies connect to business objectives. Findings reach stakeholders in the format they need, regardless of who attended which meeting. |
|
Findability Of Research |
Hard. The slide deck is buried in a shared drive. The Confluence page has not been updated. A new product manager makes a decision without knowing the research exists. |
Research is searchable and surfaced contextually. When a new initiative starts that relates to past research, Prism surfaces relevant findings. Institutional memory works. |
|
Proving research value |
Very Hard. You have no record of whether research influenced any decision. When leadership asks “what has the research team delivered?”, the answer is a list of studies completed, not impact created. |
Quantifiable. You can show exactly which studies influenced which decisions, which stakeholders acted on findings, and where research investment created measurable business value. |
|
Researcher experience |
Researchers produce excellent work that disappears into shared drives. They rarely learn whether their findings influenced anything |
Researchers are notified when their work drives action. They see the connection between their effort and business outcomes |
|
AI synthesis |
None. |
Tiered AI synthesis designed for executive consumption. Quick summaries, study syntheses, cross-study analysis, and full strategic briefs. All verified by researchers before reaching stakeholder |
|
Cross-study insights |
Requires a researcher to manually remember or search for related studies, then manually synthesise findings. This rarely happens under workload pressure. |
AI cross-study analysis identifies patterns, contradictions, and consensus across multiple studies. What would take a researcher days is available in minutes, then verified by the team. |
Prism vs. general-purpose AI tools
Some teams use ChatGPT, Claude, or Gemini to summarise research. This helps individual researchers work faster, but it does not solve the organisational problem of connecting research to decisions.
| General Purpose AI | Prism | |
|---|---|---|
|
What it produces |
A summary of whatever document you paste in. Useful for individual productivity. No connection to business context, objectives, or stakeholders. |
Synthesis tied to business objectives. AI knows which strategic priority the research relates to, who the decision owner is, and what format the output should take for that stakeholder. |
|
Verification |
None built in. The researcher reads the output and decides whether to trust it. No structured verification workflow. No certification process. No audit trail. |
Researcher verification and certification is required. AI drafts. Humans verify, add nuance, and certify. Executives see a verified brief, not raw AI output. The audit trail shows who verified what. |
|
Cross-study patterns |
You can paste multiple documents into a prompt, but the AI has no persistent memory of your research portfolio. Each session starts from zero. You cannot ask “what do our last five studies say about this topic?” |
Cross-study analysis draws from your entire research portfolio. Prism identifies contradictions, consensus, and gaps across studies. The AI synthesis is grounded in your organisation’s evidence base, not a single document. |
|
Decision infrastructure |
None. A ChatGPT summary does not create a decision artefact, track who acted on findings, or notify the researcher when their work influenced a strategic call. |
Every synthesis connects to the decision infrastructure. Named decision owners. Decision tracking. Impact measurement. The synthesis is not the end product. The decision it informs is. |
|
Security |
Research data is pasted into a third-party consumer tool. Data handling policies vary. Enterprise controls may not be available. Sensitive research may not be appropriate to share. |
Your research stays within the platform. Enterprise security. Data does not leave your environment. Appropriate for sensitive competitive, pricing, and strategic research. |
