One agentic platform.
Your entire data stack.

Data engineering, analysis, and science in collaborative multiplayer workspaces for humans and agents.

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Alkera works with the applications and tools you already use.

AWSObject storage
BigQueryData warehouse
ConfluenceKnowledge source
DatadogObservability
FivetranData ingestion
GitHubCode & CI/CD
HexData analysis
LookerBusiness intelligence
NotionKnowledge source
RedshiftData warehouse
SlackCommunication
SQLiteDatabase
TrinoQuery engine

AI needs more than access to your data.

Each knowledge entry shows its sources and whether it is human-verified.

Column-level lineage across warehouse, transformation, and analysis.

Test changes safely in sandbox environments.

Analyze in notebooks. Share as dashboards.

Use the Alkera agent to create rich analyses in SQL and Python notebooks, then share them as interactive dashboards. Change an input and only the numbers and charts that depend on it recalculate.

Learn more

Run heavy jobs
on dedicated GPUs.

Give a notebook's kernel a dedicated GPU node to train and post-train models, then chart the results in the same notebook.

pretrainCell 5 · Python

config = LlamaConfig(hidden_size=2048, num_hidden_layers=24,
                     num_attention_heads=16, max_position_embeddings=4096)
model = FSDP(LlamaForCausalLM(config), mixed_precision=bf16_policy,
             device_id=torch.cuda.current_device())

for step, batch in enumerate(loader):  # 8 GPUs, 1M tokens per step
    loss = model(**batch).loss
    loss.backward()
    clip_grad_norm_(model.parameters(), 1.0)
    optimizer.step(); scheduler.step(); optimizer.zero_grad()

8x NVIDIA B200

Work together, live.

Your team and its agents collaborate on chats and notebooks in shared workspaces. Share dashboards and other artifacts with teammates, and they update live.

Revenue review

Priya

Can you chart monthly revenue by segment for this year?

Used 2 notebook tools

Done. Enterprise is growing fastest, about 5% a month, and drives most of the year’s growth.

Ranq3-revenue.alknb.py3 cells · finished

Marcus

Nice. Can we split it by region too?

Adding a region facet to the trend chart now.

Editingq3-revenue.alknb.py1 cell

trendCell 6 · Python

alkera.chart(revenue).line(
    x="yearmonth(month)", y="sum(revenue)", color="segment",
).title("Monthly revenue by segment").tooltip().facet("regAlkera agent

Bring Alkera into your data stack.

Start for free Book a demo

Read the documentation

One agentic platform.Your entire data stack.

Alkera works with the applications and tools you already use.

Bring Alkera into your data stack.

One agentic platform.
Your entire data stack.