Artificial Societies

What do they actually do

Artificial Societies sells a web app that simulates how a defined audience will react to a message, post, product idea, or pitch. You describe or connect an audience, the product assembles AI personas into a social graph, runs a short simulation where personas see and influence each other, and returns scores plus written summaries, comments, and example reactions. It can also auto‑generate and test multiple content variants in one run (societies.io; Business Wire).

Today it’s used by marketers, founders/creators, PR teams, and product teams who want faster, lower‑cost feedback than live A/B tests or recruited panels. Plans include a free tier (3 starter credits) and a Pro plan at $55/month or $40/month billed annually; there’s also an enterprise tier with custom audiences, API/CRM integrations, and account support (societies.io).

The team is adding vertical templates (PR, social, fundraising) and has shown discrete simulations like a VC “Wave” audience for pitch refinement. They raised a seed round reported around $5.3M in mid‑2025 to expand enterprise features and pursue market‑research and enterprise customers (Business Insider; Business Wire; HN demo thread).

Who are their target customer(s)

• Growth marketers / social media managers: Need quick, low‑cost checks on whether a post, headline, or campaign will land before spending on ads or risking organic reach; full A/B tests or recruited panels aren’t feasible for every idea.
• Founders and fundraisers: Want to refine pitch language and outreach to investors or customers without burning leads or signaling misalignment; lack time and access for large real‑world tests.
• PR and communications teams: Must anticipate reactions from different audience segments and journalists; traditional testing is slow and expensive, and a misstep can lead to negative or missed coverage.
• Product managers and small product teams: Need fast feedback on feature ideas and messaging to judge product‑market fit without building prototypes or running lengthy user studies.
• Agencies and consultants (marketing/insights): Have to deliver repeatable recommendations across many clients under tight timelines; recruiting panels and running bespoke studies for each brief is costly and slow.

How would they acquire their first 10, 50, and 100 customers

• First 10: Hands‑on founder outreach to YC alumni, early investors, and portfolio companies; run white‑glove, no‑cost pilots where the team builds audiences, runs simulations live, iterates on‑call, and converts outcomes into short case studies and testimonials (societies.io; Business Insider).
• First 50: Push the free plan (3 starter credits) through targeted demos/workshops in startup and marketing communities; pair each session with ready‑made templates (PR, VC pitch, social post) and follow with conversion sequences using the first‑10 case studies (societies.io).
• First 100: Pilot partnerships with 3–5 agencies (discounted multi‑client seats, co‑branded reports) and short paid pilots for mid‑market PR/product teams with exportable reports and CRM proof‑of‑concept; back with tight SLAs and clear upgrade paths to Pro/enterprise.

What is the rough total addressable market

Top-down context:

Direct TAM is market research/insights at roughly $90–100B annually; adjacent PR/communications adds about $100B and social‑media management another ~$20–25B. Digital ad spend (~$734B in 2024) is upper‑bound context, not directly addressable (TBRC market research; TBRC PR; Grand View Research; TBRC digital ads).

Bottom-up calculation:

With Pro priced at ~$660/year per seat, ~15k paying users equates to ~$10M ARR; a mix of 20–50k Pro users yields ~$13–33M ARR, and ~200 enterprise deals at ~$25k each would add ~$5M—suggesting a near‑term SAM in the low tens of millions at current pricing (societies.io pricing).

Assumptions:

• Pro ARPU is ~$660/year based on $55/month list pricing.
• Early adopter pool across marketers, founders, PR and product teams can reach 20k–50k globally via self‑serve.
• Enterprise ACV of ~$25k for custom audiences, integrations, and support.

Who are some of their notable competitors

• Delve AI: Builds AI personas and synthetic users for chat, surveys, and interviews; focuses on persona‑driven research rather than networked, social‑graph simulations (site; synthetic research).
• Native AI: Offers large‑scale digital twins and an always‑on market‑intelligence platform oriented to enterprise data integration, not multi‑agent influence modeling (site).
• Lakmoos: Provides validated AI panels/synthetic respondents with compliance and benchmarking; competes as a fast, auditable alternative to traditional survey panels (site).
• Evidenza: Synthetic market‑research sprints producing playbooks and rapid A/B outputs; overlaps on message testing but leans into structured research deliverables (site).
• Synthetic Users: Replaces qualitative interviews with AI interviewees and scripted study workflows for UX/product teams, rather than modeling social influence between personas (site).