Your team spends hours every week hunting for answers that already exist somewhere inside your organisation — buried in Slack threads, Confluence pages, GitHub pull requests, Google Drive folders, and email chains. GiiS.ai connects every data source, runs a six-stage retrieval pipeline grounded in your actual documents, and surfaces the right answer in under 35 seconds — with inline citations back to the source. Not a guess. The answer.
Built on GiiS Search (the enterprise RAG engine that beat ChatGPT Enterprise 64–76% of the time across 99 real workplace questions) and GiiS Flow (the visual AI workflow builder trusted by AWS, Accenture, and Deloitte). GiiS combines both into a single, self-hostable AI platform your team will actually use.
Most enterprise AI tools run a single search pass and hand the results directly to the LLM. That approach produces hallucinations and misses critical context. GiiS runs a structured six-stage pipeline that filters noise before the LLM ever sees it — the same pipeline that produced a 23% recall improvement and 343 ms median retrieval across 6.8 million document chunks.
let you try the product with your own data, in your own environment, before any money changes hands. No demo. No slides. The real thing, with your actual documents and your actual questions.
GiiS Chat is not a wrapper around a single LLM. It is a model-agnostic interface that connects to every major AI model — and to every piece of knowledge your organisation has ever created. Every conversation is grounded in your actual data, not training data from the public internet.
On a scale of 1 to 10 — how much time does your team lose every week because the right information is not instantly accessible?
GiiS Agents are not chatbots with a system prompt. They are fully configurable AI workers that understand your organisation's specific context, can take actions in external systems, reason across multiple steps to complete complex tasks, and proactively engage users when relevant information surfaces. Each agent is a deployable, shareable unit with its own knowledge base, tool access, and analytics.
GiiS is not a stack of features — it is a system of interlocking capabilities. Remove any one layer and the accuracy, security, or productivity advantage collapses. Here is exactly what each capability gives you, and what happens the moment it is gone.
| Capability | What it gives you | What happens without it |
|---|---|---|
| 6-Stage RAG Pipeline | 64–76% win rate over every major competitor. Answers grounded in your actual documents, not hallucinated from training data. | Single-pass search. No LLM selection, no context expansion. Competitors outperform you on accuracy. Hallucination risk rises sharply. |
| Permission-Aware Connectors | ACLs from Confluence, Jira, GitHub, Google Drive, Slack, Salesforce, SharePoint sync automatically. Users only retrieve answers from sources they are authorised to see. | Manual ACL management. Information oversharing incidents. Compliance violations. Security team says no to deployment entirely. |
| Human-in-the-Loop (HITL) | Agents only act after a human approves. Full audit trail on every decision. Required for compliance in regulated industries. | Autonomous agents act without oversight. Errors propagate into external systems (CRM writes, Jira tickets, emails sent). No audit trail for regulatory review. |
| MCP Server + Rich APIs | Your team's unstructured knowledge available from Cursor, Claude Desktop, and any AI tool that supports MCP. All AI tools share the same context. | Each AI tool is siloed. Your coding assistant does not know what your support agent knows. Your team re-explains context repeatedly across every tool. |
| 40+ Live Indexed Connectors | Continuous background sync across every connected source. Instant cross-source search. Works even when a source system is slow or down. | 10+ separate tool subscriptions. No cross-source search. Paying for redundant capabilities. Answers limited to a single system at a time. |
| Visual Workflow Builder (GiiS Flow) | Drag-and-drop multi-agent workflow orchestration. Build, test, and deploy AI pipelines without writing infrastructure code. YAML export for version control. | Every new workflow requires engineering resources. Iteration cycle measured in sprints, not minutes. AI automation stays a prototype forever. |
Connect every tool your team uses in under five minutes per source using OAuth or API key. GiiS continuously indexes connected sources in the background — incremental syncs mean your knowledge base is always up to date. Unlike MCP-based retrieval, GiiS's indexed connectors return instant cross-source results, work when a source system is down, and enforce permissions automatically.
| GiiS Indexed Connectors | MCP (Live Query) | |
|---|---|---|
| Cross-source search | ✓ Instant, across all sources simultaneously | ✗ One source per query |
| Permission sync | ✓ Automatic ACL sync from source | ✗ No permission sync |
| Works when source is down | ✓ Index is always available | ✗ Fails if source is unavailable |
| Speed | ✓ 343ms median across 6.8M chunks | ✗ Slow — live network request per query |
| Rate limit resilience | ✓ No dependency on source API limits | ✗ Fails under rate limiting |
| Setup time | ✓ OAuth or API key — under 5 min | Varies by implementation |
Let us be direct. Here is every pain point GiiS is built to solve, and exactly how it solves each one.
There is no fake countdown timer on this page. We will not pretend a price increase is happening at midnight tonight. Here is the honest truth: GiiS is in its early adopter cohort right now. The teams who sign up during this window lock in current pricing permanently — even as we add features, scale infrastructure, and raise prices for new customers as the product matures.
You should make this decision rationally. Here are the reasons teams hesitate — and, when you are ready, the specific reasons those hesitations do not hold up against the evidence.
The most powerful AI platform is worthless if your team has to context-switch to use it. GiiS integrates directly into Slack, exposes an MCP server for AI-native tools like Cursor and Claude Desktop, and provides a full API surface for developers who want to build on top of the platform.
Tell us your specific concern. We will tell you exactly how GiiS addresses it — and if we can resolve it, we want you to start today.
The question is not whether GiiS is right for your team — it is which deployment model fits your infrastructure and compliance requirements. Both paths start with a free account.
You have probably been here before. A product that looked transformative in a demo, worked beautifully in a sandbox, and then quietly failed to deliver once it met your real data and your real team. We know that experience. It is why teams hesitate even when the evidence is compelling.
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