One AI-ready data layer across every system in your estate.
NexusOne is the cross-estate control plane that makes mainframe, warehouse, lake, cloud, and SaaS sources behave as one governed surface. Agents see full context. Sensitive data never leaves your perimeter. No migration required.
Your AI program is stuck on the data layer underneath the model, not on the model itself.
Every team trying to move AI agents into production hits the same wall, and it's not which AI model they picked. The blocker is the data layer behind the model. Models can only reason from the context they're given, and the context lives across mainframes, Teradata, Cloudera, three clouds, a policy admin system, and a Snowflake or Databricks footprint that doesn't see any of them.
Most data platforms running production AI today were specified before any of this was a requirement. So vector stores, agent frameworks, and model servers get bolted on the side, each with its own identity model, its own ACL, and its own audit trail.
There’s a better way.
The data layer your agents need is the one that already covers every system you own, governs them all the same way, and lets agents reason across them without sensitive data ever leaving your perimeter.
AI agents and LLMs need an AI-native data solution
01 · One control plane across the entire estate
One composable control plane to deploy anywhere and own your data and compute
Mainframe. Teradata. Cloudera. Snowflake. Databricks. S3. The SaaS sources of record. The lakehouse you just stood up. All federated under one catalog, one identity, one policy model. Agents reason across the estate the way a senior analyst would. Not against a single warehouse pretending to be the whole company.
02 · Airgapped where regulation or risk demands it
One universally consistent security policy applied to every agent and user
Inference, embeddings, vector indexes, retrieval, agent state, traces, and evaluation data run inside the boundary you own. On-prem, sovereign cloud, or hybrid. The platform deploys with no outbound path when the workload calls for it. Classified, OT, and disaster-recovery environments included.
03 · Governance and access defined once, enforced everywhere
One operational model for all your data, regardless of where it lives.
Row, column, tag, and policy enforcement applies to a human analyst and an AI agent the same way, from the same identity backbone. Agents inherit the permissions of the user they act for. Every query, prompt, retrieval, and tool call lands in the audit log your data team already trusts.
04 · Full context to the model without the data leaving the perimeter
One complete semantic model of your business from every system in your estate.
Agents get the catalog, the lineage, the business semantics, and the governed data behind a question. They get what they need to answer well. None of it leaves a boundary you control.
Move from a stack of disconnected AI bolt-ons to one AI-ready data layer in weeks.
NexusOne doesn't replace your core, your warehouse, or your legacy Hadoop. It lays over them.
Your data estate today
Vector stores, agent frameworks, and model servers bolted onto whichever cloud each team picked first.
Every new AI workload comes with its own identity model, its own ACL, and its own audit trail.
Agents can only reason against the one room they were pointed at. Mainframe and Teradata stay invisible.
Sensitive data leaves your perimeter the moment a hosted model gets called.
Prompts and retrieved documents land in vendor logs you don't run and can't easily audit.
No FinOps model for token spend, no circuit breakers, no central registry. Nobody knows what an agent did last Tuesday.
60–80% of your data team's time goes to Kerberos, upgrades, and pipeline maintenance.
Regulators find data drift before your reporting team does. POCs sit in pilot purgatory.
With NexusOne
One layer federates every source behind one catalog, one identity, one policy model.
AI serving with lineage, audit trail, and human-review checkpoints regulators can inspect.
Inherit Hadoop, Spark, and warehouse workloads as-is without rewrites.
Patches, upgrades, and access policy run on the platform, not on your headcount.
Credit, claims, and PII never leave your VPC or your region.
Per-agent FinOps, a central agent registry, and automated circuit breakers for runaway agents.
The platform runs the patches, upgrades, and policy changes. Your engineers ship products.
Automated lineage testing catches data quality failures before they reach a report or a model.
Power AI applications and use cases with NexusOne
Platform + People + Automation
Superior data technology
A composable, open data layer that lays over your existing stack. One catalog and identity model across the estate. Iceberg-native storage. Sovereign agent and LLM runtime. Kubernetes-native, on-prem, cloud, or hybrid. Same architecture in every site, including air-gapped.
Forward-deployed engineers
Forward-deployed engineers who have stood this up inside Tier-1 banks, telcos, and credit bureaus. They sit with your teams, deploy in your environment, and deliver production outcomes. Not slide decks.
AI/ML-enabled operations
HDFS-to-Iceberg in one click. Kafka-free CDC. Schema translation. Policy generation across systems that never spoke before. Dynamic agent governance and circuit breakers. Months of plumbing, done in minutes.
Built for the work your team has to ship next quarter, not next decade
Achieve an AI-ready data layer in weeks, not years
5 hours
Deploy NexusOne. Launch the control plane in your VPC or air-gapped site. Federate existing identities. Import discovered policies.
5 days
Connect mainframe, warehouse, Hadoop, cloud, and SaaS into one catalog. Lineage live. First governed data products and embeddings shipping.
5 weeks
Production AI. Semantic layer, agent-ready endpoints, retrieval pipelines, MRM scaffolding, and human review running against your priority use case.
A Tier-1 global bank replaces legacy Hadoop and funds its AI agenda with the savings.
Ten-plus years of credit, risk, and transaction history on a sprawling Hadoop estate. Every modernization proposal on the table demanded a multi-year rip-and-replace — right as the bank was rushing to stand up its first production AI use cases.
$30M+
Cloudera license costs eliminated
$100M+
Hardware savings via serverless
30 Apps
Modernized for AI in under 4 weeks
0
Data leakage outside governed boundary
The Result
NexusOne laid a composable layer right over existing Hadoop and warehouses. Existing workload persisted, HDFS migrated to Iceberg formats with automated utilities and Spark jobs continued to run while delivering an AI-ready data layer to power consumer LLM assistant use cases.
The bank is now zeroing out legacy Hadoop license spend, safely decommissioning obsolete hardware, and running production AI on a sovereign fabric.
Built on open standards, governed for production, ready for AI.
Your agents are already running. Is your data layer ready to govern them?
The enterprises getting AI into production are the ones who sorted out the data layer underneath before a regulator, an audit, or an incident forced the issue. That's the work NexusOne is built for.
Keep what's working
Mainframe, Hadoop, Teradata, warehouse, lake, and cloud stay where they are.
Design for open, sovereign data
Data, models, prompts, embeddings, and audit trails stay inside your boundary.
Build in air-gapped, 360 Agent governance
Full context to the model, one identity for humans and agents, FinOps and circuit breakers built into the layer.
FAQs
How is this different from Snowflake Cortex, Databricks Agent Bricks, or any AI built into our warehouse?
Cortex and Agent Bricks are destinations inside one warehouse. NexusOne is the layer across them and across the mainframe, the lake, the cloud warehouse you don't run, and the SaaS sources of record. Our customers run Cortex and Agent Bricks. We're how their agents see the rest of the company at the same time. The estate is converging on open formats. Databricks acquired Tabular, Snowflake open-sourced Polaris, and NexusOne is the control plane across the converged surface.
We already have a vector DB and an agent framework. Why do we need another data layer?
Those are model-side. The data layer is what makes them safe and useful at production scale. Without one control plane across the estate, every retrieval index, agent transcript, and model log is its own perimeter with its own identity. NexusOne gives the same governance to a vector store, a Trino query, a Kafka topic, and a mainframe extract.
Won't this introduce another abstraction layer that will leak?
We're a control plane built on the same open formats your tools already speak. Iceberg, Arrow, Parquet, Trino, Gravitino, Kubernetes. 85+ open-source tools deeply integrated, not a homegrown fork. If you ever leave NexusOne, you take your storage and your data in open formats.
Can we build this ourselves on open source?
You can. Doing so takes 18–24 months, eight senior engineers, and a running tax on every patch and upgrade. Our automation layer removes that tax. You keep the open-standards foundation without inheriting the maintenance.
How does it stay sovereign when our agents call external models?
Local LLMs and embedding models run inside the control layer on hardware you control. When a workload calls for a hosted model, NexusOne enforces the same row, column, and tag policy on what crosses the boundary, masks PII in flight, and lands every call in the audit log. The decision of what may leave is yours, not the agent's.
How does the cost compare to what we run today?
Simple vCore pricing, fully managed, with enterprise discounting on top of rack rate. In most engagements NexusOne is net cost reduction before counting the AI upside, because we let you sunset legacy license and hardware spend that was funding the old stack.