Dimension Labs

Industry

Constituent and member feedback analytics for public services and nonprofits

Read every call, chat and survey from the people you serve. Find which process failures block enrollment and service, in every language.

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Ask Which process failures block enrollment?

We work with enterprises such as NBA, Travelers, Mars and Concentrix.

[01] The problem

When the process fails, people call. Every call explains the failure.

Public programs and nonprofits handle surges of conversations around deadlines and emergencies. The patterns that would fix the process are rarely analyzed while they still matter.

Right now

01Call surges are staffed, not analyzed
02Multilingual feedback is read in one language only
03Process failures are found after the deadline
04Reports to boards and funders are built by hand
05Chatbot and phone channels are measured separately

Every enrollment question is a signal about where the process breaks.

[02] EnrichOne record, structured

Language in. Structured data out.

Every record is read in full and written back with dozens of typed Dimensions, the same way every run. Here is what that looks like for public sector and nonprofit.

enrichment · one record

Raw text

My coverage ends Friday and I uploaded my income documents twice. The portal keeps saying they're missing. I can't go without insurance for my kids.

Enrollment chat · applicant · case joined

Dimensions written to the record

Urgency & Deadlinecoverage ends Friday
Effort Levelhigh · duplicate uploads
Digital & App Experiencedocuments not recognized
Escalation Riskhigh
Emotional Intensityhigh
Customer Segmentfamily coverage

Each colour links a phrase in the raw text to the Dimensions extracted from it. Hover either side.

[03] The product

3.1 · Read everything

Every record, enriched.

Start with one export of calls, chats, emails and surveys in any language, or connect every channel. Every record comes back with typed Dimensions like urgency and deadline, effort level, digital and app experience, escalation risk and customer segment, written the same way every run, then joined to case, program, region and outcome data.

Read every record, not a sample
Join each record to case, program, region and outcome data
Add your own Dimensions in plain English
Backfill years of history in the same run

dimension labs · blend

3.2 · Prove the cause

Ask why. Get proof.

Ask in plain English. The agent writes the queries, controls for what would confound the answer, and ranks each issue by its measured effect on enrollment, resolution and retention, with an effect size and a confidence interval. Findings that fail the robustness checks are never reported as causal.

Which process failures block enrollment
Read every language on the same Dimensions
Find surges before the deadline, not after
Produce the board and funder report on schedule

dimension labs · ask

Example finding

Which process failures block enrollment?

Process failures ranked by their effect on completed enrollment, with the conversations behind each one.

Every channel · case data joined

3.3 · Deliver

Ask for the report. Get the report.

Ask for the readout your board and funders needs and the agent builds it: summary, ranked findings, charts and recommendations, each figure checked. Schedule it weekly or monthly on fresh data, or publish it as a live monitor.

Produce the monthly readout without building it
Publish a live monitor leadership can open and question
Track whether the fix you shipped moved the number
Export to PDF, slides or your BI tool

dimension labs · report

[04] How the platform worksRuns daily

From raw conversations to a proven answer.

Language from every channel and your business data flow into one pipeline that enriches, governs and tests every record, then delivers wherever your team works.

Language · 37 sources

ZendeskIntercomSalesforceLiveChatDriftSlackQualtricsMedalliaSurveyMonkeyQuestionProGenesysAmazon ConnectAvaya Cloud8x8TwilioSMSAdaKore.aiYellow.aiCognigyRasaMicrosoft Bot FrameworkAmazon LexAmazon AlexaOracle Digital AssistantBotcopyCapacityFacebook MessengerKikX (Twitter)OpenAIEmailCall recordingsApp store reviewsGoogle reviewsOpen-ended surveysCommunity forums

Business + world data

SnowflakeDatabricksBigQueryAmazon S3Salesforce CRMCSV + ExcelREST APIRevenueOrdersRenewalsUsage eventsLoyaltyStore + location dataWeatherSeasonalityMarket events

Dimension Labs pipeline · Runs daily

Ingest + normalizeEvery channel and language into one schema

EnrichDozens of Dimensions written onto every record

Map + governValidated for drift, versioned, the same fields every run

Analyze + proveJoined to outcomes and tested for cause

Where it goes

Dimension Labs agentAsk, report, schedule

Your warehouseSnowflake, Databricks, BigQuery

BI toolsTableau, Power BI, Hex

Claude and ChatGPTvia MCP · coming soon

[05] ArtifactsBuilt by the agent