Liva AI
Licenses real human conversation data and social-intelligence evals for teams training AI that reads emotion, intent, and context.
Liva AI is a data-and-evals vendor, not a tool you sign into. The homepage splits the offering cleanly: request the existing dataset catalog, or discuss a custom project for a specific research problem — both routed through contact rather than a checkout. That makes it a fit for labs and enterprise model teams with a defined training or evaluation gap, and a poor fit for anyone wanting a self-serve download. The differentiator worth weighing is the evals work alongside the data: measuring social intelligence objectively is harder than sourcing audio, and pairing ground-truth interaction data with a way to score models is the part most data vendors don't attempt. Compare against general
Verified 12d ago · liveness 61/100 · cite: rightaichoice.com/tools/liva-ai
- Research labs developing novel models for human-AI interaction
- Enterprise teams deploying conversational AI in real-world settings
- Model teams needing human interaction data for post-training
- Teams that need objective evals of social intelligence, not just more data
- Teams looking for a logged-in analytics or meeting-notes product
- Video-first or non-conversational data needs
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Skip Liva AI if you want to browse and buy a dataset today without a scoping conversation — the homepage routes everything through requesting the catalog or discussing a custom project.
Custom dataset creation is scoped per project, so budget depends on the research problem you bring rather than a listed rate — define scope narrowly before you start.
Liva AI's pricing fits teams whose volume aligns with the published tiers. Compare against the alternatives listed below for stage-specific value.
In short
Liva AI — Licenses real human conversation data and social-intelligence evals for teams training AI that reads emotion, intent, and context. Best for Research labs developing novel models for human-AI interaction, Enterprise teams deploying conversational AI in real-world settings, Model teams needing human interaction data for post-training. Contact Sales pricing.
What people actually say about Liva AI — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
37 mentions across 3 sources (Hacker News, YouTube, Lemmy) · researched Aug 11, 2026.
Average across the 3 sources that answered — each source counts once, not each post.
- +Focuses on emotional and nuanced voice data missing in synthetic alternatives.
- +Offers custom dataset creation for specific research and model needs.
- +Provides speaker diarization and emotion labels per utterance.
- +Covers multilingual and code-switching scenarios, valuable for global teams.
- +Includes domain-specific data for customer service, sales, and tutoring.
- −No community reviews or real-world usage reports to validate quality.
- −Lacks transparent pricing; contact-only model creates friction.
- −Hacker News dismisses it as a shallow YC AI startup.
- −No integration details; likely a manual data delivery process.
- −Emotion data ethics and consent may complicate compliance.
- • No public pricing; likely requires sales calls and custom contracts
- • Licensing fees may include usage restrictions
- • Custom dataset creation may carry setup costs
Viability Score
How well maintained and how widely used is Liva AI? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- Social intelligence research drawing on psychology and philosophy
- Social intelligence evals that define and measure good model behavior
- Objective ways to measure social intelligence in existing models
- Human interaction data for post-training AI models
- Human interaction data for evaluating AI models
- Existing dataset catalog available on request
- Custom data creation scoped to a specific research problem
- Ground-truth data sourced from real human interactions
- Data covering context, intent, emotion, relationships, and timing
- Datasets covering how interactions evolve over time
- Work with research labs developing novel human-AI interaction models
- Work with companies deploying AI in the real world
- Backed by LinkedIn and X
About Liva AI
Liva AI is a data and evaluation partner for teams building socially intelligent AI. Instead of shipping a product your team logs into, it supplies the raw material: real human interactions for post-training and evaluating models, datasets built to a specific research problem, and objective evaluations of what "good" social intelligence actually looks like. The public work spans three areas — social intelligence research drawing on psychology and philosophy, social intelligence evals that measure existing models, and human interaction data. The company says it works with research labs developing novel models for human-AI interaction as well as companies deploying AI in the real world, positioning itself between how models are built and how people want to interact with them. The premise running through the material is that social intelligence requires more than parsing what people explicitly say: models need context, intent, emotion, relationships, timing, and how an interaction evolves. Liva treats real human interactions as ground truth. Access runs two ways per the site — request the existing dataset catalog, or discuss a custom project scoped to a specific research problem. Buyers are research labs, enterprise speech groups, and model teams that need authentic audio and interaction data rather than synthetic corpora. Backed by LinkedIn and X.
Behind the Verdict
The pitch on theliva.ai is narrower and more specific than the category it usually gets filed under. Liva is not selling speech datasets in bulk; it is selling social intelligence — research, evaluations, and human interaction data as three connected workstreams. The site's framing is that studying how humans understand one another (drawing on psychology and philosophy) produces the ground truth that both the datasets and the evals are built from. That structure matters for buyers. If your problem is "we need more audio," plenty of vendors solve it. If your problem is "our model handles customer frustration, joking, disagreement, or a shift in register badly, and we have no objective way to know whether we fixed it," then the evals component is the interesting part. Objective measurement of social intelligence is genuinely difficult, and few data vendors attempt it — most stop at handoff. Who it fits: research labs working on human-AI interaction, and companies deploying conversational AI where getting tone wrong has real cost. The site states it works across both sides, which is a defensible position — labs need benchmark-grade data, deployers need data that reflects actual customer behavior. Where to be careful. The public page is deliberately high-level: it describes the three work areas and two engagement paths but does not publish a catalog, dataset volumes, language coverage, label taxonomy, or license terms on the homepage. Everything substantive runs through "request our catalog" or "discuss a custom project," so your evaluation happens in a conversation, not a browser. That is normal for licensed training data and it means diligence matters more than page-scraping: ask for the label schema, the consent and privacy basis, and sample data before committing. The seed profile notes sample data available for evaluation before licensing — confirm that is still offered. One thing the homepage does not do is promise a subscription product, integration surface, or API access. Read it as a procurement exercise: scope, legal review, license terms. Teams expecting a trial signup will be looking in the wrong place.
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Real-world workflow fit
Concrete scenarios for the personas Liva AI actually fits — and what changes day-one when you adopt it.
You are post-training a conversational model and your synthetic dialogue corpus produces responses that miss tone and intent. You request Liva's existing dataset catalog and evaluate sample data against your failure cases before licensing.
Outcome: You license human interaction data as ground truth, so the model learns from real exchanges covering context, relationship, and timing rather than generated approximations.
Your deployed assistant handles customer conversations but nobody can say objectively whether it got better after the last training run. You commission social-intelligence evals against your model's outputs.
Outcome: You get an objective measurement of social intelligence for your model, which turns "it feels better" into a number you can track release over release.
Your roadmap needs data for a research problem no existing dataset covers — a specific interaction type your users keep hitting. You open a custom project conversation rather than shopping a catalog.
Outcome: You get data scoped to the problem you actually have, built with real human interactions as the reference standard.
Use Cases
- Post-train a conversational model on real human interactions rather than synthetic dialogue.
- Evaluate whether an existing model reads intent and emotion correctly using objective social-intelligence evals.
- Commission datasets for a specific research problem around human-AI interaction.
- Ground a model's behavior in real interactions where tone, timing, and relationship context matter.
- Study how interactions evolve over time to improve multi-turn conversational quality.
- Source human interaction data as the reference standard for a social-intelligence benchmark.
Limitations
- The public homepage is intentionally high-level: it describes three work areas and two engagement paths, but does not publish dataset volume, language coverage, label taxonomy, or license terms.
- Everything substantive runs through requesting the catalog or discussing a custom project, so your evaluation happens in a conversation rather than in a browser.
- The site lists no integrations, API surface, or developer documentation, so do not assume a programmatic delivery path.
- As a data licensing arrangement, expect the engagement to run through procurement and legal review rather than a product signup.
- The seed profile also notes the platform does not support analysis of music or non-speech audio, and that customization and on-premise deployment likely require enterprise agreements.
as of 2026-09-26
Verification history
We have re-verified Liva AI 9 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-checked, vendor evidence unchanged
- — re-checked, vendor evidence unchanged
- — re-checked, vendor evidence unchanged
- — re-checked, vendor evidence unchanged
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 9 verification passes.
Free to cite with attribution — this page re-verifies continuously.
Where the pricing makes sense
The company stage and team size where Liva AI's pricing actually pencils out — and where peers do it cheaper.
Liva AI's pricing fits teams whose volume aligns with the published tiers. Compare against the alternatives listed below for stage-specific value.
Setup time & first value
How long it actually takes to get something useful out of Liva AI — broken out by persona, not the marketing-page minute.
There is no signup flow to estimate: you either request the existing dataset catalog or open a conversation about a custom project. Expect days to weeks before first value, because the timeline is driven by catalog review, sample evaluation, scope definition, and legal review of the license rather than by onboarding steps. Budget the procurement and privacy review as the critical path.
Switching to or from Liva AI
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From synthetic-only training corpora: request the catalog, evaluate sample data against your model's failure cases, then license real human interactions as ground truth.
- →From a generic audio dataset vendor: bring the specific social-intelligence gap that volume alone didn't fix and scope a custom project around it.
- →From in-house data collection: replace ad-hoc recording efforts with licensed human interaction data plus objective social-intelligence evals.
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “Liva AI”, and we withheld 6: 6 could not be judged, because “Liva AI” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Liva AI.
Official links
Tools that pair well with Liva AI
Common stack mates teams adopt alongside Liva AI, with the specific reason each pairing earns its keep.
David AI
Audio datasets built like research artifacts for teams training speech recognition, translation, synthesis and voice-interaction models
Panels
Custom audio datasets for training and evaluating voice AI, scoped to your model's spec.
ds-ml-bootcamp
Open Somali AI datasets and speech models — SomNLP-Corpus, whisper-som ASR, and SomBench benchmarks from Somast.
Featured Head-to-Head Comparisons
Liva Ai vs Splice
Splice and Liva AI serve completely different purposes. Splice is a sample library and plugin rental platform for music producers starting at $4.99/mo, while Liva AI is an enterprise transcription and analysis tool with contact-based pricing. Choose Splice if you need royalty-free sounds or want to rent Serum 2; choose Liva AI if you need to turn meeting audio into structured insights.
Liva Ai vs Landr Mastering
LANDR Mastering is the practical choice for musicians needing fast, affordable mastering with a free preview tier and album-wide consistency. Liva AI targets a completely different use case — enterprise meeting analysis — so choose based on whether you need audio polish or conversation insights. For music production, LANDR is the clear winner.
Liva Ai vs Storyfile
StoryFile and Liva AI serve entirely different needs. StoryFile creates authentic, interactive video conversations from real people for museums and legacy preservation—recently proven with high-profile deployments like Kara Swisher’s digital twin for CNN and George Takei at the Japanese American National Museum. Liva AI focuses on extracting insights from meeting and call recordings. Pick StoryFile if your goal is to bring a real person’s likeness and voice into conversational AI; choose Liva AI if you need to analyze business conversations for actions and sentiment.
Alternatives to Liva AI
View all
David AI
Audio datasets built like research artifacts for teams training speech recognition, translation, synthesis and voice-interaction models
Panels
Custom audio datasets for training and evaluating voice AI, scoped to your model's spec.
ds-ml-bootcamp
Open Somali AI datasets and speech models — SomNLP-Corpus, whisper-som ASR, and SomBench benchmarks from Somast.
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