High Quality Datasets To Train Next Gen AIs

We collect and curate datasets based on your unique needs, to truly differentiate your AI models.

Trusted by Lead ML & AI Teams

Our Services

High Quality AI Training Data

Need quality data to train or fine-tune models? Ta-da delivers image, audio, video, and text datasets—collected, annotated, and ready to use.

For any data type

  • Audio

  • Video

  • Image

  • Text

For any data type

  • Audio

  • Video

  • Image

  • Text

For any data type

  • Audio

  • Video

  • Image

  • Text

Train your AI with specifically dedicated data

Your AI models are only as good as the data they're trained on. Differentiate your AI with bespoke datasets.

From data collection, to labeling

Our community of crowd workers and data analysts all work together towards 1 goal: bringing the best possible data to your project.

Need data?

We collect, label, and deliver datasets built for your AI goals.

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Need data?

We collect, label, and deliver datasets built for your AI goals.

|

Need data?

We collect, label, and deliver datasets built for your AI goals.

|
  • class SentimentTrigger:
    def __init__(self, threshold):
    self.threshold = threshold
    # Threshold for positivity score
    self.status = "neutral"
    def analyze_sentiment(self, score):
    if score > self.threshold:
    self.status = "positive"
    return "Positive sentiment detected!"
    elif score < -self.threshold:
    self.status = "negative"
    return "Negative sentiment detected!"
    else:
    self.status = "neutral"
    return "Neutral sentiment."
    def get_status(self):
    return f"Sentiment status: {self.status}"

  • class SentimentTrigger:
    def __init__(self, threshold):
    self.threshold = threshold
    # Threshold for positivity score
    self.status = "neutral"
    def analyze_sentiment(self, score):
    if score > self.threshold:
    self.status = "positive"
    return "Positive sentiment detected!"
    elif score < -self.threshold:
    self.status = "negative"
    return "Negative sentiment detected!"
    else:
    self.status = "neutral"
    return "Neutral sentiment."
    def get_status(self):
    return f"Sentiment status: {self.status}"

  • class SentimentTrigger:
    def __init__(self, threshold):
    self.threshold = threshold
    # Threshold for positivity score
    self.status = "neutral"
    def analyze_sentiment(self, score):
    if score > self.threshold:
    self.status = "positive"
    return "Positive sentiment detected!"
    elif score < -self.threshold:
    self.status = "negative"
    return "Negative sentiment detected!"
    else:
    self.status = "neutral"
    return "Neutral sentiment."
    def get_status(self):
    return f"Sentiment status: {self.status}"

  • class SentimentTrigger:
    def __init__(self, threshold):
    self.threshold = threshold
    # Threshold for positivity score
    self.status = "neutral"
    def analyze_sentiment(self, score):
    if score > self.threshold:
    self.status = "positive"
    return "Positive sentiment detected!"
    elif score < -self.threshold:
    self.status = "negative"
    return "Negative sentiment detected!"
    else:
    self.status = "neutral"
    return "Neutral sentiment."
    def get_status(self):
    return f"Sentiment status: {self.status}"

  • class SentimentTrigger:
    def __init__(self, threshold):
    self.threshold = threshold
    # Threshold for positivity score
    self.status = "neutral"
    def analyze_sentiment(self, score):
    if score > self.threshold:
    self.status = "positive"
    return "Positive sentiment detected!"
    elif score < -self.threshold:
    self.status = "negative"
    return "Negative sentiment detected!"
    else:
    self.status = "neutral"
    return "Neutral sentiment."
    def get_status(self):
    return f"Sentiment status: {self.status}"

  • class SentimentTrigger:
    def __init__(self, threshold):
    self.threshold = threshold
    # Threshold for positivity score
    self.status = "neutral"
    def analyze_sentiment(self, score):
    if score > self.threshold:
    self.status = "positive"
    return "Positive sentiment detected!"
    elif score < -self.threshold:
    self.status = "negative"
    return "Negative sentiment detected!"
    else:
    self.status = "neutral"
    return "Neutral sentiment."
    def get_status(self):
    return f"Sentiment status: {self.status}"

Train smarter, scale faster

Ta-da works with leading AI teams to source custom data for next-gen models—while ensuring compliance with the latest AI standards.

Tailored data for AI Agents

We provide custom training datasets, robust evaluation pipelines, and rich contextual environments to help AI agents learn, adapt, and perform safely in real-world scenarios.

Instruction

Provide high-quality datasets to train and evaluate AI agents

across different use cases. Include dialogues, edge cases,

environments, and evaluation metrics.


Input files:

Multi_Turn_Conversations.json

Edge_Case_Secnarios.docx

Simulated_Env_Data.csv

Instruction

Provide high-quality datasets to train and evaluate AI agents

across different use cases. Include dialogues, edge cases,

environments, and evaluation metrics.


Input files:

Multi_Turn_Conversations.json

Edge_Case_Secnarios.docx

Simulated_Env_Data.csv

Instruction

Provide high-quality datasets to train and evaluate AI agents

across different use cases. Include dialogues, edge cases,

environments, and evaluation metrics.


Input files:

Multi_Turn_Conversations.json

Edge_Case_Secnarios.docx

Simulated_Env_Data.csv

Here's What Our Customers Say

Real businesses, real results.

“At BdSound, we recognize that the single most crucial factor for the success of an AI project lies in having high-quality, meticulously verified real-world data. Ta-da’s verification process impressed us, and we are delighted to collaborate with them in collecting data for our new applications in speech enhancement and voice recognition.”

Michele Buccoli

Senior Innovation Scientist @BdSound

“At BdSound, we recognize that the single most crucial factor for the success of an AI project lies in having high-quality, meticulously verified real-world data. Ta-da’s verification process impressed us, and we are delighted to collaborate with them in collecting data for our new applications in speech enhancement and voice recognition.”

Michele Buccoli

Senior Innovation Scientist @BdSound

“At Identt, precision in identity verification is absolutely critical. Thanks to the high-quality, verified datasets provided by Ta-da, we significantly improved our document recognition models and reduced validation errors. Their thorough annotation process and diverse data sources played a key role in the success of our KYC systems."

Aleksandra Nowak

Head of Product @IDENTT

“At Identt, precision in identity verification is absolutely critical. Thanks to the high-quality, verified datasets provided by Ta-da, we significantly improved our document recognition models and reduced validation errors. Their thorough annotation process and diverse data sources played a key role in the success of our KYC systems."

Aleksandra Nowak

Head of Product @IDENTT

“At Identt, precision in identity verification is absolutely critical. Thanks to the high-quality, verified datasets provided by Ta-da, we significantly improved our document recognition models and reduced validation errors. Their thorough annotation process and diverse data sources played a key role in the success of our KYC systems."

Aleksandra Nowak

Head of Product @IDENTT

Customer Case Studies

Helping the most ambitious AI teams and corporations build smarter.

DRAG TO EXPLORE

DRAG TO EXPLORE

AI-enhanced vocal data improved assistant accuracy by 30%

A leading tech company building voice assistants needed high-quality, multilingual voice data to improve understanding across accents and commands. Ta-da delivered annotated audio datasets at scale, enabling faster model training and higher voice recognition accuracy.

Impact :

30% Fewer Misunderstood Commands

50+ Languages and Accents Covered

40% Faster Training Time

25% Boost in Intent Recognition Accuracy

AI-enhanced vocal data improved assistant accuracy by 30%

A leading tech company building voice assistants needed high-quality, multilingual voice data to improve understanding across accents and commands. Ta-da delivered annotated audio datasets at scale, enabling faster model training and higher voice recognition accuracy.

Impact :

30% Fewer Misunderstood Commands

50+ Languages and Accents Covered

40% Faster Training Time

25% Boost in Intent Recognition Accuracy

AI-labeled ID data reduced onboarding errors by 35% for a Fintech platform

A leading KYC provider struggled with mismatches and verification delays due to inconsistent identity document data. Ta-da sourced and annotated thousands of real-world ID samples, helping the AI model learn edge cases, improve OCR accuracy, and accelerate identity checks.

Impact :

35% Fewer Onboarding Errors

40% Faster Identity Verification

80+ Countries’ ID Formats Covered

25% Increase in Auto-Approval Rates

AI-labeled ID data reduced onboarding errors by 35% for a Fintech platform

A leading KYC provider struggled with mismatches and verification delays due to inconsistent identity document data. Ta-da sourced and annotated thousands of real-world ID samples, helping the AI model learn edge cases, improve OCR accuracy, and accelerate identity checks.

Impact :

35% Fewer Onboarding Errors

40% Faster Identity Verification

80+ Countries’ ID Formats Covered

25% Increase in Auto-Approval Rates

Custom AI conversations improved support resolution time by 45%

Synapse, a conversational AI provider, needed rich, multilingual dialogue data to boost chatbot performance. Ta-da delivered labeled conversations, edge-case prompts, and realistic interactions—enabling smarter, faster, and more natural AI responses.

Impact :

45% Faster Support Resolution

30% Improved Intent Accuracy

25 Languages Covered

50,000+ Humanlike Conversations Delivered

Custom AI conversations improved support resolution time by 45%

Synapse, a conversational AI provider, needed rich, multilingual dialogue data to boost chatbot performance. Ta-da delivered labeled conversations, edge-case prompts, and realistic interactions—enabling smarter, faster, and more natural AI responses.

Impact :

45% Faster Support Resolution

30% Improved Intent Accuracy

25 Languages Covered

50,000+ Humanlike Conversations Delivered

Different needs, different datasets

On-demand collection & labeling

Specify your needs, and we design data collection and/or labeling campaigns tailored to your project: content, crowd, QC methodology: there is no limit to your creativity

Off-the-shelf datasets

More than 10 000 hours of high quality, annotated voice datasets in different languages and with speakers from select accents are available to train your next voice AI agent

We have many more datasets

Activity Detection

Biometrics

Wake Words

Speech Recognition

OCR Images

Infrastructure

Voice Commands

Waste Detection

Vehicles and Traffic

Face Recognition

Object Detection

Synthethic Data

Threat Detection

Our Key Benefits

How we can help you

Humans in the Loop

Access to a network of millions of vetted contributors: industry experts, annotators, linguists, actors, voice talents...ready to power your AI with precision.

Humans in the Loop

Access to a network of millions of vetted contributors: industry experts, annotators, linguists, actors, voice talents...ready to power your AI with precision.

Humans in the Loop

Access to a network of millions of vetted contributors: industry experts, annotators, linguists, actors, voice talents...ready to power your AI with precision.

Project Management Included

Every project is led by experienced managers who ensure quality, timeline, and communication—so you can focus on results, not micromanagement.

Project Management Included

Every project is led by experienced managers who ensure quality, timeline, and communication—so you can focus on results, not micromanagement.

Project Management Included

Every project is led by experienced managers who ensure quality, timeline, and communication—so you can focus on results, not micromanagement.

Secure & decentralized

Our interfaces, security standards, and distributed ledger technology are designed to ensure your data is sourced in ethical, secure and confidential ways

Secure & decentralized

Our interfaces, security standards, and distributed ledger technology are designed to ensure your data is sourced in ethical, secure and confidential ways

Secure & decentralized

Our interfaces, security standards, and distributed ledger technology are designed to ensure your data is sourced in ethical, secure and confidential ways

How we work

  1. Contact us

  1. Contact us

Reach out through our platform or email—our team is ready to assist you in no time.

Reach out through our platform or email—our team is ready to assist you in no time.

  1. Explain Your Need

  1. Explain Your Need

Tell us about your project and the type of data you need. The more detail, the better.

Tell us about your project and the type of data you need. The more detail, the better.

  1. Our Data Analysts Provide Solutions

  1. Our Data Analysts Provide Solutions

Our experts will assess your requirements and propose the best dataset strategy—custom collection, annotation, or sourcing.

Our experts will assess your requirements and propose the best dataset strategy—custom collection, annotation, or sourcing.

  1. Get Your Data, Train Your AI

  1. Get Your Data, Train Your AI

Receive high-quality, ready-to-use data and start training your models with confidence.

Receive high-quality, ready-to-use data and start training your models with confidence.

High Quality AI Training Data

Need quality data to train or fine-tune models? Ta-da delivers image, audio, video, and text datasets—collected, annotated, and ready to use.

High Quality AI Training Data

Need quality data to train or fine-tune models? Ta-da delivers image, audio, video, and text datasets—collected, annotated, and ready to use.