Your data speaks different languages.
Every source has its own structure, identifiers, definitions, and version of the truth.
The Agentic Data Stack
Where your databecomes context.And contextbecomes outcomes.
Data lands. The ontology forms. Moby goes to work.
Native warehouseLive ontologyAgent harness
Native data + agent runtime
The warehouse is inside the harness.
Most agents inherit someone else’s data model. Moby ingests the mess, discovers the schema, builds the ontology, and keeps it current—inside the same system it uses to act.
A data team and an infra team—in a box.
01IngestEvery source, continuously
02InferMeaning forms as data lands
03PreserveState, history, and truth
04ActMoby executes the work
The bottleneck
AI can reason. It just doesn’t know your business.
Models are intelligent. Your company’s context is fragmented across hundreds of systems, schemas, documents, decisions, and people. That gap is where useful AI breaks.
People become the integration layer.
The real ontology lives in meetings, spreadsheets, tribal knowledge, and one operator’s head.
Without context, AI can only assist.
It can draft and suggest. It cannot reliably understand state, use the right tools, or own an outcome.
The system
From raw data to executed work.
The data foundation and agent runtime are one system. Data arrives, meaning is inferred, context stays current, and Moby can work against it immediately.
01
Data in
Sensory
Bring in the signals that describe your business: structured, unstructured, internal, external, real-time, and historical.
SourcesWarehouses · SaaS · docs
ModesBatch · stream · event
OutputObservable raw signal
02
Context inferred
Saber 2
Normalize the mess. Infer entities and relationships. Build the ontology on the fly. Orchestrate efficient pipelines that adapt as the business changes.
EngineSemantic inference
BuilderPipeline + ontology graph
OutputTrusted business context
03
Work done
Moby
Query the business in natural language, assemble step-by-step workflows, or deploy agents that reason, use tools, and learn.
HarnessTools · memory · state
ControlPermissions · approvals
OutputMeasured outcomes
Connected by default
Every system your business runs on.
Bring commerce, advertising, lifecycle, fulfillment, finance, and warehouse data into one context layer—without rebuilding the stack around your agent.
100+technology partners60+ native integrations
Warehouse connectivity
Moby meets your data where it already lives.
Connect the warehouse already at the center of your stack to the same living context layer. Moby can then reason and act against governed business data.
Built on Triple Whale infrastructure
Moby is built on the same production foundation proven across more than $100 billion in GMV.
$100B+GMV supported
$30BAd spend supported
14TRows scanned
15TRows updated daily
Broader integration ecosystem
Amazon EU
Amazon FE
Amazon NA
ShopifyCurrent public integration ecosystemExplore all integrations ↗
Saber 2
Watch the ontology build itself.
As data lands, Saber 2 discovers the schema, resolves identity, infers relationships, creates business concepts, and keeps the graph current. No months-long modeling project between your data and your agent.
S2
owner_id · segment
lifecycle_stage
lifecycle_stage
arr · term · status
renewal_date
renewal_date
feature · frequency
last_active
last_active
role · influence
relationship
relationship
sentiment · severity
resolution
resolution
risk_score · signal
next_best_action
next_best_action
● schema detected crm.accounts
● identity resolved account_id
● relation inferred uses_product
● metric compiled health_score
The native warehouse
Context has somewhere to live.
As data arrives, Moby builds the structure around it—schema, history, permissions, relationships, and state—inside the same system it uses to work.
Moby
Ask a question. Build a workflow. Deploy an agent.
Moby is the first agent harness designed around a natively integrated data and ontology layer—with the tools, state, memory, permissions, and feedback loops required to own an outcome.
01
Find every account with hidden churn risk
Running02
Research the cause across product, support, and CRM
Running03
Build a recovery plan for each account
Complete04
Draft the right action for the right owner
Approval05
Measure what changed and improve the playbook
MonitoringWhat you can build
Every data-heavy function becomes programmable.
Revenue operations
Enrich accounts, prioritize pipeline, keep CRM state clean, prepare outreach, and coordinate handoffs.
+Customer intelligence
Connect product usage, support history, commercial context, sentiment, and relationship signals into one live view.
+Business operations
Reconcile systems, investigate anomalies, route decisions, generate reports, and keep records synchronized.
+Marketing execution
Analyze performance, create campaigns, coordinate content, manage budgets, and learn from the outcome.
+Your internal operating system
Turn the proprietary way your company works into reusable context, policies, workflows, and agents.
+The model is ready. Now the data is too. All the inference is done for you, so the AI can just work.
Your data + infra teams in a box
Build the Agentic Data Stack.
Connect the company. Let Saber 2 infer the map on the fly. Put Moby to work with the database, ontology, and agent harness already integrated.
Request early access ↗For teams building the next operating system for their business.