Train, evaluate, deploy & observe specialized language models
Datawizz accelerates the transition to specialized language models - from data collection & decomposition, SFT/RFT, model deployment, evaluation and run-time observability. Close the loop faster, improve continuously.
About
About
About
Building
specialized
language models
today
means
exporting
production
data by hand,
reformatting
it for training,
fighting with
CUDA versions
and PyTorch
dependencies,
building
eval sets from scratch,
and then shipping
with no easy way
to compare,
rollback,
or catch regressions.
Datawizz handles
all this
infrastructure,
so you can
focus on
making
your AI
app better.
Building
specialized
language models
today
means
exporting
production
data by hand,
reformatting
it for training,
fighting with
CUDA versions
and PyTorch
dependencies,
building
eval sets from scratch,
and then shipping
with no easy way
to compare,
rollback,
or catch regressions.
Datawizz handles
all this
infrastructure,
so you can
focus on
making
your AI
app better.
Building
specialized
language models
today
means
exporting
production
data by hand,
reformatting
it for training,
fighting with
CUDA versions
and PyTorch
dependencies,
building
eval sets from scratch,
and then shipping
with no easy way
to compare,
rollback,
or catch regressions.
Datawizz handles
all this
infrastructure,
so you can
focus on
making
your AI
app better.
Benefits
Benefits
Benefits
Why it’s worth growing with Datawizz
Infrastructure on Autopilot
We handle the infra. You just use it.
Infrastructure on Autopilot
We handle the infra. You just use it.
Infrastructure on Autopilot
We handle the infra. You just use it.
Ship Faster
Go from production logs to retrained model in hours, not weeks.
Ship Faster
Go from production logs to retrained model in hours, not weeks.
Ship Faster
Go from production logs to retrained model in hours, not weeks.
Focus on your AI App
Spend time improving your app, not debugging integrations.
Focus on your AI App
Spend time improving your app, not debugging integrations.
Focus on your AI App
Spend time improving your app, not debugging integrations.
How It Works
How It Works
How It Works
Building your own Specialized Language Model is as simple as that
Datawizz Integration
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from openai import OpenAI
client = OpenAI(
api_key="sk-your_openai_api_key", # <--- your datawizz project API key
base_url="https://gw.datawizz.app/**************/openai/
v1", # <--- your datawizz project base URL
)
response = client.chat.completions.create(
model="********", # <--- this is the DataWizz Endpoint you
are routing to,
messages=[
{
"role": "user",
"content": [
{"type": "text", "text": "What's the speed of light?"},
],
}
]
)
Datawizz Integration
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from openai import OpenAI
client = OpenAI(
api_key="sk-your_openai_api_key", # <--- your datawizz project API key
base_url="https://gw.datawizz.app/**************/openai/
v1", # <--- your datawizz project base URL
)
response = client.chat.completions.create(
model="********", # <--- this is the DataWizz Endpoint you
are routing to,
messages=[
{
"role": "user",
"content": [
{"type": "text", "text": "What's the speed of light?"},
],
}
]
)
Integrate
Datawizz deploys into your existing application - no code changes needed
Datawizz Integration
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from openai import OpenAI
client = OpenAI(
api_key="sk-your_openai_api_key", # <--- your datawizz project API key
base_url="https://gw.datawizz.app/**************/openai/
v1", # <--- your datawizz project base URL
)
response = client.chat.completions.create(
model="********", # <--- this is the DataWizz Endpoint you
are routing to,
messages=[
{
"role": "user",
"content": [
{"type": "text", "text": "What's the speed of light?"},
],
}
]
)
Datawizz Integration
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from openai import OpenAI
client = OpenAI(
api_key="sk-your_openai_api_key", # <--- your datawizz project API key
base_url="https://gw.datawizz.app/**************/openai/
v1", # <--- your datawizz project base URL
)
response = client.chat.completions.create(
model="********", # <--- this is the DataWizz Endpoint you
are routing to,
messages=[
{
"role": "user",
"content": [
{"type": "text", "text": "What's the speed of light?"},
],
}
]
)
Open-weights Model - 7B
Open-weights Model - 13B
Open-weights Model - 40B
Datawizz Integration
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from openai import OpenAI
client = OpenAI(
api_key="sk-your_openai_api_key", # <--- your datawizz project API key
base_url="https://gw.datawizz.app/**************/openai/
v1", # <--- your datawizz project base URL
)
response = client.chat.completions.create(
model="********", # <--- this is the DataWizz Endpoint you
are routing to,
messages=[
{
"role": "user",
"content": [
{"type": "text", "text": "What's the speed of light?"},
],
}
]
)
Request
Language
English
French
Model A
Model B
Open-weights Model - 7B
Open-weights Model - 13B
Open-weights Model - 40B
Datawizz Integration
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from openai import OpenAI
client = OpenAI(
api_key="sk-your_openai_api_key", # <--- your datawizz project API key
base_url="https://gw.datawizz.app/**************/openai/
v1", # <--- your datawizz project base URL
)
response = client.chat.completions.create(
model="********", # <--- this is the DataWizz Endpoint you
are routing to,
messages=[
{
"role": "user",
"content": [
{"type": "text", "text": "What's the speed of light?"},
],
}
]
)
Request
Language
English
French
Model A
Model B
Route
Use Datawizz to route requests to different models based on content, topic, task or size - getting the best result every time.
Datawizz Integration
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from openai import OpenAI
client = OpenAI(
api_key="sk-your_openai_api_key", # <--- your datawizz project API key
base_url="https://gw.datawizz.app/**************/openai/
v1", # <--- your datawizz project base URL
)
response = client.chat.completions.create(
model="********", # <--- this is the DataWizz Endpoint you
are routing to,
messages=[
{
"role": "user",
"content": [
{"type": "text", "text": "What's the speed of light?"},
],
}
]
)
Request
Language
English
French
Model A
Model B
Datawizz Integration
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from openai import OpenAI
client = OpenAI(
api_key="sk-your_openai_api_key", # <--- your datawizz project API key
base_url="https://gw.datawizz.app/**************/openai/
v1", # <--- your datawizz project base URL
)
response = client.chat.completions.create(
model="********", # <--- this is the DataWizz Endpoint you
are routing to,
messages=[
{
"role": "user",
"content": [
{"type": "text", "text": "What's the speed of light?"},
],
}
]
)
Request
Language
English
French
Model A
Model B
Train
Datawizz fine-tunes Specialized Language Models based on your data
Open-weights Model - 7B
Open-weights Model - 13B
Open-weights Model - 40B
82% Accuracy
90% Savings
91% Accuracy
80% Savings
96% Accuracy
70% Savings
Open-weights Model - 7B
Open-weights Model - 13B
Open-weights Model - 40B
Request
Language
English
French
Model A
Model B
Open-weights Model - 7B
Open-weights Model - 13B
Open-weights Model - 40B
82% Accuracy
90% Savings
91% Accuracy
80% Savings
96% Accuracy
70% Savings
Open-weights Model - 7B
Open-weights Model - 13B
Open-weights Model - 40B
Request
Language
English
French
Model A
Model B
Open-weights Model - 7B
Open-weights Model - 13B
Open-weights Model - 40B
82% Accuracy
90% Savings
91% Accuracy
80% Savings
96% Accuracy
70% Savings
Open-weights Model - 7B
Open-weights Model - 13B
Open-weights Model - 40B
75%
25%
Open-weights Model - 13B
Open-weights Model - 7B
Open-weights Model - 13B
Open-weights Model - 40B
82% Accuracy
90% Savings
91% Accuracy
80% Savings
96% Accuracy
70% Savings
Open-weights Model - 7B
Open-weights Model - 13B
Open-weights Model - 40B
75%
25%
Open-weights Model - 13B
Deploy
You can choose to deploy a model to production - no code changes
82% Accuracy
90% Savings
91% Accuracy
80% Savings
96% Accuracy
70% Savings
Open-weights Model - 7B
Open-weights Model - 13B
Open-weights Model - 40B
75%
25%
Open-weights Model - 13B
82% Accuracy
90% Savings
91% Accuracy
80% Savings
96% Accuracy
70% Savings
Open-weights Model - 7B
Open-weights Model - 13B
Open-weights Model - 40B
75%
25%
Open-weights Model - 13B
Get Started Now
Integrating Datawizz takes under 15 minutes.
