Data silos
Enterprises run 10–50+ agents in parallel. Moving data between fragmented systems is the primary bottleneck — disconnected context produces bad AI results.
Control your data.
Power your AI.
OmniFabric unifies all your enterprise data, knowledge and intelligence on infrastructure you fully control — so AI runs on trusted data without ever leaving your jurisdiction.
Trusted by data & AI teams shipping production agents
Intelligence
Flywheel
Flywheel
Agent
Model
Data
Native vector search
Decision lineage captured
One fabric for the modern data & AI stack
Amway
Tencent
Stone Castle
Mercury Insurance
Olsera
JST
The reality
AI is the new productivity engine — but there is a business gap
AI is racing ahead, from passive chatbots to autonomous agents. Adoption isn't the gap — turning it into enterprise ROI is.
90%
Employees using AI at work, personally
40%
Firms with an official enterprise AI rollout
5%
Enterprise GenAI pilots with measurable P&L impact
Source: MIT NANDA · State of AI in Business 2025
ChatGPT doesn't know your business.
General AI is brilliant but lacks your private context. Without your data, AI is just a high-IQ stranger in your office.
- Internal SAP / ERP transactional records
- Proprietary legal & compliance data
- Real-time supply chain & inventory logs
- Unstructured email & sales conversations
Four data realities block AI from reaching production at scale
Unstructured chaos
Traditional databases can't see the ~80% of business knowledge locked in documents, email and media. AI-native platforms must treat documents as data.
Brittle ETL
Connecting models to data needs glue code that breaks constantly. Each new agent becomes a multi-month engineering project, and complexity grows exponentially.
Security & trust
Mission-critical AI demands sovereignty and governance: protected PII, end-to-end traceability, reproducible outputs — and an “undo” for bad decisions.
The intelligence flywheel
Agent · Model · Data — unified in one fabric
Traditional stacks bolt a vector store, a model gateway, and an orchestration layer onto a legacy database. OmniFabric collapses them into a single hyper-converged platform where each layer makes the others smarter.
One source of truth
A cloud-native, hyper-converged engine unifies transactional and analytical workloads with native vectors — no ETL sprawl, no stale copies.
Any model, governed
Route to any LLM or embedding model through one surface, with every call wrapped in a context snapshot and full audit lineage.
Agents that improve
Production agents learn from implicit feedback, retain long-term memory, and self-evolve behind regression gates — safely, in production.
10–100×
Faster agent delivery — weeks, not months
30–70%
Lower TCO — no redundant systems or data copies
100%
Auditability — every AI decision traced to its data
$0
To start — pay-as-you-go, no license, no minimum
Data sovereignty
Your data and AI never leave your control
For regulated and mission-critical workloads, OmniFabric runs where your data must live — your region, your infrastructure, your rules. Full residency, deployment flexibility, and end-to-end governance, built in.
Regional data residency
Your data and models stay in-region by default, meeting local data-residency and sovereignty requirements.
Deploy anywhere
Run on local cloud, on-prem, or hybrid edge — the same platform, wherever compliance requires.
Unified governance
RBAC, full audit trails, and snapshotting for every AI-driven outcome — no black-box decisions.
Compliance-ready
Protect PII, trace every decision end-to-end, and reproduce any result for legal and regulatory sign-off.
Real business ROI
Turn AI strategy into measurable outcomes
When data, models, and agents share one fabric, work that took days collapses into seconds — and the numbers show up on the bottom line.
80%
Training efficiency · retail
Legal teams surface risk clauses instantly instead of reading line by line.
≈10×
Bid production · manufacturing
Documents are parsed, structured, and written back automatically.
−15%
Procurement cost · telecom
Routine reporting and reconciliation handled by trusted agents.
100×
Résumé screening · energy
Proposals assembled from the knowledge base in a fraction of the time.
Why OmniFabric
One fabric beats a stack of point solutions
Hyperscalers sell you five services to wire together; legacy platforms give you a database and stop there. OmniFabric is one platform you own — unified, sovereign, affordable, and self-improving.
All-in-One
Data, vectors, models, and agents in a single platform — no glue code, no five-vendor stack to operate.
Sovereignty
Run in your cloud, on-prem, or air-gapped. Your data and models stay under your control, in your region.
Cost-Effective
One bill, no inter-service egress, no per-feature SKUs — cut total cost of ownership dramatically.
Self-Evolution
Agents learn from production feedback and improve behind regression gates — value compounds over time.
| Dimension | OmniFabric | Open-source self-built | Cloud hyperscalers | Snowflake / Databricks |
|---|---|---|---|---|
| Architecture | Unified at the architecture level — native HTAP, one data copy | Many OSS parts, stitched by you | Separate services — not natively linked | Unified product; OLTP added by M&A, no native HTAP |
| Engineering effort | Low — natively integrated, all-in-one | Highest — build & run it all | High — you write the glue & governance | Moderate — multi-engine sync, add-on AI |
| Sovereign deploy | Any infra — sovereign-cloud native | Any infra, but self-operated | Locked to their cloud | Mostly their managed cloud |
| AI & models | Open-source or commercial — no lock-in | Integrate models yourself | Their model garden | Closed models only |
| Pricing / start | Pay-as-you-go · $0 to start | Free software, high ops cost | Complex per-service + egress | Premium |
Customer stories
Teams ship faster when one fabric backs every decision
We retired our separate vector database and ETL jobs. Search, analytics, and our agents now read the same live data — with no stale copies and nothing extra to operate.
TencentAI platform team
Decision lineage was the unlock. Every agent action is explainable and reversible, so compliance signed off and we went to production in weeks, not quarters.
Stone CastleInvestment firm
Contract review went from over two weeks to about a minute. The knowledge base keeps itself current, so our analysts focus on judgment, not data entry.
Mercury InsuranceInsurance carrier
Case studies
From pilot to production across industries
TencentTechnology
+40%
feature reuse
A unified multimodal data & feature platform
Teams stopped rebuilding the same models — cross-department feature reuse rose 40% and dev cycles shrank 30%.
AI platform team
Read case study
OlseraRetail SaaS
10×
faster insights
Real-time analytics for every merchant
High-volume transaction data analyzed in real time — instant merchant insights and copilots.
Retail POS platform
Read case study
AmwayRetail · Direct selling
80%
higher training efficiency
An AI training assistant for new-product rollouts
Internal case material and product docs unified into an AI assistant — marketing staff self-learn how to promote new products instead of months of group training.
Amway Nutrilite
Read case study
JSTManufacturing
≈10×
faster bid production
A bidding agent that drafts proposal packages
Bidding materials and historical cases power an agent that assembles bid packages in 1–2 days instead of 1–2 weeks.
JST Power Equipment
Read case study
Stone CastleFinance
80%
analyst time freed
Automated investment research at scale
Research automated across 60+ data sources freed about 80% of analyst time for strategy.
Investment firm
Read case study
Mercury InsuranceInsurance
16d → 1m
claims review
Instant claims & policy risk review
Risk-clause review collapsed from 16 days to about a minute, and the knowledge base stays current.
Insurance carrier
Read case study
Solutions
Built for the workloads that matter most
One fabric powers a range of high-value, production AI applications.
Document intelligence
Contract review, claims, and compliance — parsed, understood, and answered with citations.
Learn moreRAG knowledge base
Support and sales agents grounded in real account data, with memory across every conversation.
Learn moreChat to data warehouse
HTAP queries over fresh operational data — dashboards and agents read the same source of truth.
Learn moreAgent development
Hybrid keyword + vector retrieval across every source, with governance built in.
Learn moreCustomer-facing copilots
Every agent decision carries lineage and audit trails regulators can inspect.
Learn moreRisk & compliance
Back-office workflows — data entry, reconciliation, reporting — run by self-improving agents.
Learn more
How it works
From evaluation to production in three steps
1
Connect your data
Point OmniFabric at your databases, files, and streams. It ingests, parses, and embeds everything into one governed fabric — no separate vector store required.
2
Compose your agents
Wire any model into agents with built-in memory and skills. Every call is snapshotted, so behavior is explainable from day one.
3
Ship & self-improve
Run safe A/B tests on live data, gate changes behind regressions, and let agents refine themselves — with rollback always one click away.
Enterprise AI strategy
From one agent to an agent workforce
AI + marketing, R&D, data, knowledge management, customer service, HR and research — on one foundation that scales from the first agent to a governed workforce.
1
First agent
Prove ROI in weeks.
2
Multiple agents
Replicate across teams.
3
Agent workforce
10–50+ agents governed in parallel.
Trusted data
Unified, governed enterprise data — the single source of truth your AI runs on.
Compute power & token service
Elastic compute and managed token services that power every model and agent.
Sovereign cloud
Infrastructure you fully control — your data and AI never leave your jurisdiction.
Weave your data and AI into one fabric
Start free, connect your first source in minutes, and ship a trusted agent the same day. Talk to us when you're ready to scale.