Prism turns a large volume of free-text responses into a structured, inspectable account of the positions people actually took — one where every figure traces back to named responses, and every claim traces back to the words it came from.
A public consultation that draws thousands of free-text responses is difficult to read honestly. Counting responses rewards whoever writes most. Summarising them by hand is slow, unrepeatable, and quietly discards the minority and the inconvenient.
The usual shortcuts — keyword tallies, sentiment scores, a sample read by an overworked team — each lose something a decision-maker needs: the actual structure of opinion, and the ability to stand behind the result when challenged.
A single comment is reduced to the discrete points it actually makes — each one a topic together with the stance the writer takes toward it. Filler and boilerplate are set aside as non-substantive: counted, but not treated as positions.
Positions that express the same idea are gathered together by resemblance of meaning, not shared keywords. The strands of opinion are not chosen from a predefined list — they emerge from what people actually wrote, and you can read them coarsely or finely as the question requires.
Within a group, positions are sorted by the stance they take — support, opposition, a proposed change — and each is shown with its strongest verbatim quotation. The result is not a single average but the internal structure of agreement and disagreement.
Every position stays linked to the exact response it came from and the specific passage of original text behind it. Nothing is asserted that cannot be checked by reading the source.
Two comments from a live US public consultation — the Federal Trade Commission's 2024 review of children's online-privacy rules — as Prism read them. Each colour marks a distinct topic the comment touched; greyed-out text is what Prism judged non-substantive and deliberately filed as nothing. Every highlight traces back to the exact words on the page.
71% of the text carried a position. The rest — the framing, the rhetoric, the closing ask — is greyed out: classified as nothing, rather than forced into a box.
81% coverage. One dominant position (blue) threaded through two related topics; the academic citations are read as substance, the connective tissue is not.
That's the span-level view of single comments. Two worked examples go further — across many commenters:
One real position-group — how children's ages should be verified — read into positions, verbatim evidence, and figures you can check.
Read →A group that looked like broad agreement was one form letter filed a dozen times — caught by traceability, not the statistics.
Read →It reads thousands of responses, but every conclusion stays checkable by a non-expert: follow any figure back to the highlighted source text and judge for yourself.
The strands of opinion and their labels come from the responses themselves, not from a codebook fixed in advance — and the level of detail is adjustable.
It preserves the structure of opinion rather than collapsing it to a score, and keeps a coherent minority view visible instead of letting volume bury it.
It reports how many distinct people stand behind a position — not merely how many statements were filed — and makes coordinated or duplicated input visible and checkable.
It organises, measures, and makes traceable; it defers contested cases to a reviewer and records its uncertainty rather than resolving it silently. A defensible starting point for a decision — not a verdict that replaces one.
Prism began as a proposal for reading public consultations — where getting the answer right, and being seen to, matters most. That origin fixed a set of commitments into how it works.
Every response stays classifiable, traceable, and retrievable. The system surfaces the whole picture; it never silently decides what a decision-maker sees.
Volume is data. A hundred messages about the same thing is a signal about severity, not a duplicate to discard.
Open methodology, documented logic, checkable figures. “Trust us” is not a transparency mechanism.
No covert processing — what's collected, how it's handled, and how to opt out are all visible.
Reading input is worthless without a visible response. The method has to connect what people said to what was done about it.
It's measured and reported, not waved away — the goal is to keep bias visible and correctable, not to pretend there is none.
The system organises; humans decide. That boundary is architectural, not just a promise.
None of this is new ground. Taiwan's vTaiwan has run citizen consultations at national scale since 2015; Decidim (Barcelona) and CONSUL (Madrid) power participatory democracy across more than a hundred cities. What changed is the input: those platforms rely on structured agree/disagree voting, while Prism reads unstructured free text — lowering the barrier to taking part, and keeping the result auditable and documented to the standard public bodies now answer to.
Prism is one of the systems we've built. If you're working with large volumes of free-text responses and need an account you can stand behind, we'd be glad to walk you through it.
info@szlamkaconsulting.com