Full stack and modular
Build or buy. Experts in the room for whichever path and stack you take.
Thesis / 01
Big Context is Big Data's biggest unlock.
Decades of accumulation. Billions invested. Yet your “modern” data stack is still illegible to AI.
Big Context & Company is full stack AI transformation for the corporate data function — powered by our Pragmatics Operating System.
Pragmatics / 02
The Semantic Layer is Dead.
Long live the semantic
layer.
Semantic Context
How you attempted to define your data
A hand-crafted partial snapshot of meaning intended to be used globally across its domain.
Limited to what’s been recorded. Almost always stale.
Pragmatic Context
What your data means in actual use
A self-maintaining system of record and reliability engine that mirrors the contextual judgement of your best data experts.
Dynamic, governed — ready for AI scale use.
Your data stack was built for a world before AI. Legacy tools like semantic layers, catalogs, ontologies, & knowledge graphs have proven insufficient for AI-scale data work. Big Context is built on a Pragmatics foundation and captures how your data is actually used in the real world.
Learn more about Open Pragmatics →Full Stack AI-Native / 03
Get your data AI ready.
hover or tap
01
Pragmatics OS
Our SOTA operating system is the engine that makes data legible to AI — finally. Built according to the Pragmatics Standard, optimized for expert-level reliability.
Learn more about Open Pragmatics →02
The Practice
Accelerated data transformations led by elite data experts & forward-deployed context engineers and architects. At your services.
Explore our AI-native data services →The Operating System / 04
From siloed systems of record and fragmented context sources, through the Pragmatic Context Layer, to AI agents
01
Siloed Data
Locked in tools
02
Virtualized Data Context Layer
Independent · Open
Pragmatics OS
03
AI Agents
Across your enterprise
A peak under the hood
01
Situational awareness for every data query
A semantic layer is a static record of what data means. A pragmatic graph is a living record of how it’s actually used in your business — it’s situational awareness as a foundation. It’s an AI-native representation of your company’s live model of meaning.
02
An always-on data workforce
Legacy records promised to stay current, but couldn’t. Ad hoc queries were rarely reusable. Big Context agents watch how data is used, capture new caveats as they emerge, catch drift the moment a metric changes, and build your latent business context like a veteran on your team.
03
Workflow-native, for your convenience
No new tools to adopt, nothing to migrate, completely yours to do as you wish. Context is delivered into the tools you already run through open protocols like MCP. The OS meets your stack where it is and disappears into it.
04
SME parity and validatability
A wrong number that looks right is worse than no number — and 90% accurate, while a breakthrough in AI is catastrophic here. Before any answer or context leaves the OS, it’s validated against evals, tests, and ground truth, traceable to its source, with low-confidence cases escalated to a human rather than guessed.
05
Expert-grade governance out of the box
Governance to your enterprise’s standards — access, policy, PII handling, full audit trail — so every answer is permissioned and traceable. All backstopped by Experts-in-the-Loop. Comprehensive intervention frameworks so that the system follows the rules and your (or our) best data people can intervene at scale. Expert judgment becomes a permanent asset instead of walking out the door.
Our Edge / 05
Neutrality to the core
Vendor-neutral by design. We win only when your outcome is achieved.
AI-native pragmatics
Full context lifecycle reliability, deeper and broader than storage alone.
Accelerated outcomes
No slow pre-work tax. Mechanized process and tools to get you there fast.