Sales
CRM account briefs, call summaries, draft proposals, follow-ups, and answers to customer requests.
Enterprise AI platform for knowledge search and document drafting
We deploy a secure enterprise AI platform on your infrastructure. Teams search internal knowledge, get answers with source citations, and create first drafts of agreements, proposals, reports, and SOPs, without sending company data to consumer chatbots.
Private workspaceSecure node
Company knowledge
Access: legal team · 12,480 documents
Which termination terms belong in our new supplier agreement?
AIAnswer from your sources
Your agreement template and procurement policy require 30 days' notice, advance-payment return terms, and liability for obligations that remain open.
01 · Agreement template02 · Procurement policy
Draft ready
Termination clause
Controls
Sources attached
Legal review required
−80%less time spent searching internal documents
95%answer accuracy on the corporate knowledge base
x8faster legal research across document collections
Your team already uses AI. Do you control the data?
A marketer pastes a campaign brief into a public chatbot, a lawyer uploads contract clauses, and a rep drops in customer emails. Company information ends up in tools nobody vetted, answer quality goes unchecked, and subscriptions spread across personal cards.
An enterprise platform keeps the capability of strong models while returning control of data, access, and quality to your company.
How the enterprise AI platform works
01
Connects your documents and systems
We index policies, agreements, SOPs, and wikis from Confluence, SharePoint, shared drives, ERP, CRM, and DMS. Existing permissions carry into the AI workspace, so employees only retrieve content they are allowed to see.
Confluence
SharePoint
1C / CRM
Files / DMS
One knowledge index
12,480 documents · permissions preserved
02
Finds the answer and shows the source
Hybrid retrieval finds the relevant passages, the model answers only from that evidence, and every conclusion links back to a specific document. If the knowledge base has no answer, the assistant does not invent one.
Which termination terms belong in our new supplier agreement?
Answer from your sources
Your agreement template and procurement policy require 30 days' notice, advance-payment return terms, and liability for obligations that remain open.
01 · Agreement template02 · Procurement policy
03
Builds a draft and sends it for review
The assistant turns approved facts into a first draft of an agreement, proposal, report, or SOP using your company template. The output is clearly marked as a draft and follows the existing human approval process.
Draft ready
Termination clause
Controls
Sources attached
Legal review required
One platform: enterprise AI assistants for every department
A governed workspace configured around your processes, documents, and policies: each department gets assistants built for its daily tasks.
Customer support
Knowledge-base answers with source links, drafted customer replies, and ticket summarization.
Legal
Contract review against company checklists, precedent search, and first drafts of standard agreements.
HR and learning
Employee onboarding, policy and benefits answers, job descriptions, and development-plan drafts.
Marketing
On-brand copy, market research, internal digests, and presentation outlines grounded in company materials.
Finance and leadership
Report summaries, executive briefs, version comparisons, and fast answers on internal policies.
Search + generation
An AI knowledge base with cited answers and first drafts
We wire in RAG: the platform indexes policies, contracts, SOPs, wikis, and conversations. Your AI knowledge base is assembled from what you already have (Confluence, SharePoint, Google Drive, CRM), with no rewriting required. The assistant retrieves the relevant evidence, produces a verifiable answer, and turns it into a first draft using your approved template.
More on RAG development →Your data
ConfluenceSharePointDrive / CRMDMS
Knowledge layer
Hybrid search, reranking, permissions, and citation control
Verifiable answer
Every conclusion is grounded in documents the employee can access
Document generation
Proposal, agreement, report, or SOP in your company template
Ready for reviewEverything employees need for daily work with AI
A familiar interface
Chat and search work like the AI tools people already know. Teams can start without a separate training program.
Files and first drafts
Upload PDFs, spreadsheets, and decks; analyze, compare, extract data, and draft documents from approved templates.
No-code assistants
Departments assemble helpers from instructions, knowledge sources, and approved tools without joining an engineering queue.
Integrations and mobile access
Web, messenger, and API access. Connect CRM, ERP, DMS, shared drives, and internal services.
Built to pass your security review
Your team can approve the architecture before a pilot: where models run, what data they can see, who has access, and how every action is logged.
Models inside your network
Qwen, LLaMA, and other open models served on your infrastructure with vLLM. Sensitive data never leaves your environment.
Roles and permissions
SSO, LDAP/Active Directory, team roles and quotas, document-level access control, and complete request logging.
Model flexibility
Local models for sensitive data, cloud models for general work. Route by policy and change vendors without rebuilding the workspace.
Why teams pick this over ChatGPT Enterprise or Glean
ChatGPT Enterprise, Copilot, and Glean give every customer the same interface and vendor rules. Gless builds around your sources, workflows, and security model: custom assistants, integrations, access policies, and a self-hosted option.
ChatGPT Enterprise and Glean set the data boundary and product limits; cost scales with every seat.
You control data, models, and access rules; the platform adapts to your workflows.
Smart corporate document search
A RAG system indexes 30K+ documents and answers natural-language questions with links to the exact source.
−80% search time
Frequently asked questions
What is an enterprise AI platform?
It is a governed AI workspace deployed for a company: employees use language models through one secure interface, while an enterprise AI assistant in each department answers from internal knowledge and drafts documents using company rules. The business controls access, data, and spend.
Which models can we use?
Open self-hosted models such as Qwen and LLaMA served through vLLM on your hardware, plus cloud models of your choice. Sensitive requests can stay on local models while general work routes to cloud models.
How does the assistant search our documents?
Through RAG: documents are indexed, retrieval finds the most relevant passages, and the model answers from that evidence with source citations. We connect Confluence, SharePoint, shared drives, ERP, CRM, and DMS without forcing you to rewrite the knowledge base.
Can it create documents, not just answer questions?
Yes. The assistant gathers facts from approved sources and creates the first version of an agreement, proposal, report, SOP, or email in your template. The output is marked as a draft and follows your existing human review process.
Is it secure enough for confidential or regulated data?
For sensitive use cases, we deploy on-premise: data stays inside your network, models run locally, access is enforced through SSO/LDAP and roles, and every request is logged. We sign an NDA and DPA before receiving production data.
How long does deployment take, and what does it cost?
A pilot on your documents can be shown in about two days. A full rollout with integrations, access control, and self-hosted infrastructure usually takes 4–8 weeks. Cost depends on user count, security requirements, and integrations; we fix the quote in writing after a scoping call. Unlike per-seat products such as ChatGPT Enterprise, the quote doesn't grow every time you hire.
Get in touch
Tell us about your task — we will suggest what AI pilot we can build and what it takes to start.
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