Your Enterprise Knowledge.
Answered in Seconds.
Enterprise knowledge is locked inside documents, SharePoint folders, and file repositories that nobody can search fast enough. Compliance officers manually trawl regulatory guidance. Underwriters spend too long finding precedents that should surface in seconds. New hires take months to reach productivity because institutional knowledge is not findable.
FD RYZE® Nexus fixes this. Our purpose-built knowledge assistant is configured for your department, connects to your existing data, and deploys on your own infrastructure to deliver grounded, traceable, role-controlled answers in seconds.
Built fast. Benchmarked hard. Priced to scale.
Accuracy
Benchmarked across two independent datasets.
Hours to Go-Live
From data access to a working assistant.
Lower Cost Than Azure
Enterprise knowledge retrieval with lower infrastructure cost.
How Nexus Turns Knowledge into Working Agents
FD RYZE® Nexus is configured around department-specific enterprise knowledge and deployed through FD RYZE® Infinity to support real operational workflows.
What FD RYZE® Nexus Delivers
Speed You Can Use. Accuracy You Can Defend.
FD RYZE® Nexus moves enterprise knowledge retrieval from slow implementation cycles to technical deployment measured in days, not months. Beyond speed, it is built for answer quality and control, with 100% Text Fidelity on Synthdog and performance 10–13 points above Azure Document Intelligence on every measured parameter. The model also delivers a $6.2K Year 1 saving per customer. RBAC is active from Day 1, every answer is traceable to its source document, and full audit trails keep data governed inside your infrastructure.
Built Different. By Design.
FD RYZE® Nexus rethinks the architecture underneath enterprise knowledge retrieval. Every layer, from how documents are extracted to how answers are verified, is built for accuracy, governance, and deployment, flexibility in regulated enterprise environments.
Dynamic VLM + OCR Routing
Every document type has an optimal extraction path. Nexus intelligently routes each document to the right method at ingestion, whether it is a scanned PDF, a structured spreadsheet, or a complex engineering drawing. The result is higher fidelity extraction across your entire document library, regardless of format or complexity.
400-Token Precision Chunking
Context is where meaning lives. Nexus uses 400-token precision chunking to preserve the boundaries between ideas ensuring that answers are drawn from coherent, complete units of information rather than fragments that span where one thought ends and another begins.
Critic Agent - Active Answer Verification
Before any answer reaches a user, the Critic Agent verifies it against the source material. This is not a confidence indicator but an active correction mechanism that retries up to 3 times on failure. Every answer that surfaces has been checked and scored. This is the difference between a system that flags uncertainty and one that resolves it.
Architecture-Agnostic Deployment
Nexus runs where your data governance requires cloud (Azure, AWS, GCP), on-premise, hybrid, or Docker. No infrastructure lock-in. No compromise on sovereignty. The deployment model adapts to your regulatory environment, not the other way around.
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Case Studies
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When Search Becomes
the Bottleneck
Every delayed search comes at a cost: slower decisions, longer onboarding, more manual review, and higher risk when critical guidance is missed. Nexus helps teams find the right answer faster, with the source context needed to trust it.
Why enterprise knowledge stays locked and what it costs
Why enterprise knowledge stays locked and what it costs
The cost of slow knowledge retrieval:
- An average manual document search takes 15 minutes
- Nexus reduces that to under 2 minutes, an 80% reduction
- A 100-person team running 10 searches a day can lose thousands of hours a year on search alone
- New hires take weeks to reach productivity because institutional knowledge is not surfaced quickly enough
- Compliance errors and audit failures often trace back to guidance that existed but was not found in time
Why the usual options create new trade-offs
Why the usual options create new trade-offs
Why existing tools do not fully solve it:
- ChatGPT and Copilot in default mode send data to third-party infrastructure, which is not acceptable for many BFSI, insurance, or healthcare use cases
- Azure Document Intelligence benchmarks at 79–80% accuracy and 59% Text Fidelity on standard datasets, which may not be enough for regulated industries
- Building internally takes 6–12 months and $150K+ in engineering investment, and create platform lock-in
- Glean costs $70K+ for a POC and $200K+ annually before deployment
Latest in Insights
FAQs
FD RYZE® Nexus is a governed enterprise knowledge assistant purpose-built for specific departments and connected to your existing SharePoint and document repositories. It delivers grounded, traceable answers with role-based access control, runs on your infrastructure, goes live in 48 hours, and is benchmarked at 89–92% accuracy with 40% lower cost than Azure.
Nexus can be described as a chatbot at the interface level, but that misses the governance, traceability, and enterprise architecture underneath. It is built to turn internal documents into reliable answers that teams can use for work where accuracy and context matter.
Copilot makes your Microsoft apps smarter, while Nexus makes your institutional knowledge accessible. Copilot helps users draft emails, summarize meetings, and work across Microsoft tools; Nexus creates purpose-built, governed knowledge assistants for specific departments, with custom scope, RBAC, and traceable answers grounded in proprietary data. They solve different problems and can work together.
Technical deployment usually takes 2–5 business days from data access to first working assistant. Client-side processes such as security reviews, procurement, data access permissions can add 1–3 weeks. We start both tracks in parallel to avoid losing calendar time.
Nexus currently connects to SharePoint, document repositories, PDFs, Word documents, spreadsheets, and folder structures. These sources cover the majority of enterprise knowledge retrieval use cases, with Salesforce, Jira, Confluence, ServiceNow, SAP, and custom API connectors on the roadmap.
Your data never leaves your infrastructure. Nexus can be deployed on your cloud environment, including Azure, AWS, or GCP, or on-premise, with RBAC from Day 1, a full audit trail on every query, no training on your data, and answers that are traceable to their source documents.
Nexus is designed for enterprise customers in BFSI, insurance, and healthcare, where data sovereignty requirements are often non-negotiable. Regulatory frameworks in these industries prohibit sending proprietary documents to third-party infrastructure. So deployment within the customer’s own environment is part of the design.
Nexus pricing is based on the assistant or department, not on the number of users. Get in touch with the team for a detailed price list and savings analysis, including the model’s 40%+ saving vs Foundry and $6.2K Year 1 saving per customer.
Nexus was tested on two public, industry-standard datasets: Cord V2 for real-world documents and Synthdog for synthetic test data. The benchmark measured six parameters: Text Fidelity, Semantic Accuracy, Numeric Reliability, Completeness, Hallucination Control, and Overall Accuracy, using the same LLM, pricing tier, and deployment region on both sides. The full methodology can be shared, and customers are encouraged to reproduce the test on their own documents.
If the pilot does not deliver, the team will explain what was found and why the expected numbers were not achieved. Pilot shortfalls are usually linked to data quality issues, which are assessed during scoping before the engagement begins. If the results do not support the case by Week 4, the pilot can stop there.
The product is ready.
The data proves it.
One department. One assistant. Four weeks. Less than the cost of one consultant-week to find out exactly where your enterprise stands on AI knowledge retrieval.