Lab Nova Longevidade and Ashoka: 1,000+ hours automated in the ecosystem mapping
How the Lab Nova Longevidade 2026 Mapping, with Ashoka, automated assessments and recommendations for hundreds of social entrepreneurs, using CORRE.SOCIAL no-code flows.
1,000+ hautomated in assessments and recommendations (~1 h each)
The process
The Lab Nova Longevidade 2026 Mapping, done with Ashoka, connects hundreds of longevity social entrepreneurs across Brazil. CORRE.SOCIAL implemented the project together with the Lab Nova team, in the implementation and consulting format, and designed it as a no-code flow: one input, processing blocks and one output.
- Input: WhatsApp interview, with the audio transcribed.
- No-code blocks: data cleansing, website integration, external and internal assessments, and recommendations with 50+ rules and AI.
- Output: e-mail sequences.
- WhatsApp interview with transcribed audio
- Data cleansing
- Website integration
- External and internal assessments
- Recommendations: 50+ rules and AI
- E-mail sequences
How it was without CORRE
Without the platform, a mapping this size depends on manual work: transcribing the interviews, cleaning the answers, writing each assessment and each recommendation. Each assessment or recommendation takes about 1 hour, and the time grows with every entrepreneur who joins. It is the typical design of a manual process that does not scale, in which the team becomes a data operator.
How it works with CORRE
The steps became blocks of a flow that the Lab Nova team follows. AI is one of the blocks, next to the rules: it writes the draft and the team reviews it. The published result is 1,000+ hours automated in assessments and recommendations, at about 1 hour each.
By the numbers
| Item | Detail |
|---|---|
| Client | Ashoka · Lab Nova Longevidade |
| Project | Lab Nova Longevidade 2026 mapping |
| Process type | Assessment |
| How we work | Implementation & consulting |
| Hours automated | 1,000+ h in assessments and recommendations (~1 h each) |
| Recommendation | 50+ rules and AI |
| Blocks used | WhatsApp interview with transcribed audio; Data cleansing; Website integration; External and internal assessments; Recommendations: 50+ rules and AI; E-mail sequences |
| Source of the number | CORRE project reports. |
| Project on the web | Lab Nova Longevidade (opens in a new tab) |
What we learned
- Receive through the channel people already use. The interview was on WhatsApp, with transcribed audio, not only in a form.
- Make the criteria explicit. The recommendation combines 50+ rules and AI. The rules show why each recommendation came out; the AI writes the draft and the team reviews it.
- Connect the flow to what the network already uses. The website integration and the e-mail sequences take the result to where people are.
- Count the hours. The case number (1,000+ hours, at about 1 hour each) comes from CORRE project reports.
See also
- Who this kind of project is forListening at scale: how networks and programs listen to hundreds of organizationsSee the page
- CaseCaptação com Causa: AI assistants that help Campinas nonprofits with grant callsRead the case
- CaseICOM at Transforma Frei Damião: field data collection from phone to database, with CORRE.SOCIALRead the case
- CaseLongeviver: financial education for longevity on WhatsApp, with CORRE.SOCIALRead the case