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A persona is an AI-generated individual within a persona group. Each one has a consistent identity, backstory, purchasing habits, and cultural context — and responds to simulations in character. Personas are not archetypes or demographic buckets. They are individuals. When you run a simulation, each persona reacts from its own perspective: a 31-year-old Cebuano woman who distrusts big telcos, loves Shopee, and is cautious about new skincare brands will respond differently to your concept than a 24-year-old Jakarta software engineer who buys primarily on impulse.

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What makes Boses personas different

Most AI personas are generic: a description shaped by assumptions rather than evidence. Boses personas are grounded in real, current consumer signals crawled from public sources in each market.
SourceWhat it contributes
Reddit (r/Philippines, r/indonesia, r/VietNam)Current consumer discourse — trending concerns, product sentiment, cultural moments
Shopee reviewsReal purchase opinions, price sensitivity, brand preferences from active shoppers
Google Play Store (GCash / Gojek / MoMo)Digital service trust, UX frustrations, fintech and super-app attitudes
Before generating personas for a market, Boses runs the ethnography pipeline to distill these sources into a cultural context snapshot. That snapshot is injected into every persona’s generation prompt — giving each persona real attitudes about specific products, pricing, trust, and digital habits rather than generic cultural platitudes.
Supported markets: PH (Philippines), ID (Indonesia), VN (Vietnam). Persona generation is only available for these three markets.

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Persona fields

Every generated persona includes the following information:
  • Full name — a culturally appropriate name for the market
  • Age — within the range you defined for the persona group
  • Gender
  • Location — city or region within the target country
  • Occupation — specific role, not just an industry label
  • Income level — low / lower-middle / middle / upper-middle / high
  • Educational background — highest level attained and field of study
  • Family situation — household composition and responsibilities
  • Day in the life — a narrative snapshot of a typical day
  • Archetype label — e.g. “The Pragmatic Saver”, “The Status Seeker”
  • Psychographic segment — VALS-style classification
  • Personality traits — a list of defining characteristics
  • Values and motivations — what drives decision-making
  • Pain points — frustrations with products, services, or the market
  • Purchase behaviour — how and where they shop
  • Buying triggers — what tips them toward a purchase
  • Brand attitudes — specific trusted and distrusted brands with reasons
  • Price sensitivity — signals indicating value-consciousness or aspirational spending
  • Digital behaviour — apps used, platforms frequented, payment methods
  • Media consumption — social platforms, content formats, influencer trust
  • Aspirational identity — how they see themselves in the future
  • Avatar — an AI-generated profile photo consistent with the persona’s age, gender, and location. Available as a URL once generation is complete.

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Generating personas

Persona generation is triggered at the persona group level. You first create a persona group with your target demographic criteria, then call the generate endpoint. 
curl -X POST https://api.temujintechnologies.com/api/v1/projects/<PROJECT_ID>/persona-groups/<GROUP_ID>/generate \
  -H "Authorization: Bearer <TOKEN>"
Generation runs as a background task and typically completes in 20–40 seconds for a group of 5 personas. The response returns 202 Accepted immediately. Poll the persona group to track progress: 
curl https://api.temujintechnologies.com/api/v1/projects/<PROJECT_ID>/persona-groups/<GROUP_ID> \
  -H "Authorization: Bearer <TOKEN>"
The generation_status field transitions through: 
pending → generating → complete
                     → failed
Once generation_status is complete, you can fetch the individual personas: 
curl https://api.temujintechnologies.com/api/v1/projects/<PROJECT_ID>/persona-groups/<GROUP_ID>/personas \
  -H "Authorization: Bearer <TOKEN>"
Boses also lazily queues a cultural context refresh when you trigger persona generation. If the active snapshot for your target market is older than 7 days, it will be refreshed in the background before personas are generated — so your personas always carry current signals.

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Persona library

When Boses generates a persona, it checks the persona library — a cross-project pool of previously generated individuals — for a close match. If a sufficiently similar persona already exists, the new persona is linked to that library record. This allows consistent individuals to appear across projects, and lets you search and reuse personas you have already validated. You can browse the library directly: 
curl "https://api.temujintechnologies.com/api/v1/library/personas?location=PH&income_level=middle&age_min=25&age_max=35"
Library personas accumulate a simulation_count — how many times they have been used in research — which is a useful proxy for how well-tested a persona’s responses are.