“Conversational AI platform” means two different things depending on who’s buying. Contact-center teams mean Rasa, Kore.ai, or Dialogflow CX for customer support automation. IT and knowledge-work teams mean the AI chat layer employees use every day — ChatGPT, Copilot, Gemini, or a self-hosted alternative like Grengin.

This guide covers the second category: enterprise AI chat platforms for internal knowledge work — the tools your employees actually open 20+ times a day to draft, summarize, analyze, and search. If you came here comparing customer-service bots, the short version is: Rasa and Kore.ai lead that category, and they’re a separate buying decision from what’s below.

The 2026 Landscape at a Glance

Platform Entry Price (per user/mo) Deployment Org Data Grounding Governance Depth Best For
ChatGPT Enterprise ~$50–60 (150-seat minimum) Vendor-hosted Limited, manual connectors SOC 2, HIPAA BAA, audit logs Frontier model access, broad adoption
Microsoft 365 Copilot $30 add-on + $36–57 base license Vendor-hosted (Azure) Deep, via Microsoft Graph Strong within M365 boundary Microsoft 365-native orgs
Google Gemini (Workspace) Bundled into $14–22 Workspace plans Vendor-hosted (Google Cloud) Deep within Workspace apps Strong within Workspace Google Workspace-native orgs
OpenWebUI Free (self-hosted) Self-hosted Manual RAG setup required Minimal, DIY Technical teams, dev/test
LibreChat Free (self-hosted) Self-hosted Manual RAG setup required Minimal, DIY Developers wanting flexibility
Grengin Self-hosted, usage-based LLM cost only Self-hosted, cloud marketplace (AWS, Azure), or managed hosting (via contacting support) Built-in semantic search over org knowledge RBAC, department budgets, audit logs Governed multi-provider AI with real context

(Pricing verified from vendor sources as of July 2026; enterprise quotes are negotiated and vary by seat count and term.)

1. ChatGPT Enterprise

OpenAI’s top commercial tier is the default first stop for enterprises chasing frontier model performance. It runs on GPT-5.4 as of March 2026, with no usage caps per user — a real distinction, since ChatGPT Plus has message rate limits and the Team plan has soft caps that can slow power users down. Enterprise removes those constraints entirely.

  • Pricing: No public list price. Reported 2026 contracts run between $50 and $60 per user per month on annual commitments of 150 seats or more, falling toward $40 at 5,000-plus seats. The floor for any deployment sits near $108,000 per year once the 150-seat minimum and mandatory annual term are factored in.
  • Governance: Audit logs covering all user activity are included as a standard feature, and data residency options across US and EU are available on Enterprise contracts — a meaningful feature for regulated industries.
  • Customization: Organizations can build tailored assistants for legal review, customer support, HR policy, or sales enablement and push them to all users through the admin console.
  • Limitation: There is no self-serve trial or free evaluation path — a sales engagement is required to begin any Enterprise evaluation. The 150-seat floor and annual-only billing also shut out mid-sized teams that want to pilot before committing.

Why Grengin is the better fit: Grengin has no seat minimum and no mandatory annual lock-in — you can start with five users or five hundred. More importantly, ChatGPT Enterprise ties your organization to one model family (OpenAI’s), while Grengin routes across OpenAI, Anthropic, Mistral, and Gemini from the same interface, so a pricing change or model deprecation on one provider’s roadmap doesn’t force a company-wide migration.

2. Microsoft 365 Copilot

Copilot is the AI layer bolted directly onto the tools most enterprises already run their day inside — Word, Excel, PowerPoint, Outlook, and Teams. Its main advantage is context: Microsoft Graph Grounding and Copilot connectors pull in emails, chats, documents, and meetings so the assistant already knows what you’re working on.

  • Pricing: The enterprise add-on is $30/user/month, though Microsoft permanently reduced the Copilot Business rate to $21/user/month for organizations under 300 users as of December 2025. That’s on top of a qualifying base license (Microsoft 365 E3 at $36/month or E5 at $57/month) — true all-in cost runs $66 to $87 per user per month depending on tier.
  • Features: Agentic multi-step editing is now generally available across Word, Excel, and PowerPoint as of 2026, and Work IQ — Microsoft’s intelligence layer — builds a semantic index from a user’s M365 content, connectors, and work patterns.
  • Limitation: Copilot is fundamentally a personal productivity layer bounded by the Microsoft ecosystem. Independent analysis found that only about 6% of organizations that piloted Copilot moved to larger-scale deployment, and it does not index knowledge across a full enterprise or reason across tools outside Microsoft 365 — it can’t connect a sales rep’s question to a Slack thread or a ticket in a non-Microsoft system.

Why Grengin is the better fit: Copilot’s context stops at the edge of Microsoft 365. Grengin’s semantic search runs over your organization’s actual knowledge and conversation history regardless of which tools generated it, and it doesn’t require every employee to be on a $36–57/month base license just to unlock AI. For organizations with a mixed tool stack — not everyone lives in Outlook and SharePoint — that’s a real cost and coverage gap Copilot can’t close.

3. Google Gemini (Workspace)

Google folded Gemini directly into Workspace rather than selling it as a separate line item. As of 2026, Gemini is included in Business Standard, Plus, and Enterprise plans, with a lighter version on Business Starter — and Google raised base Workspace prices 17 to 22 percent to absorb the cost, rather than charging per-seat on top.

  • Pricing: No standalone AI surcharge. Workspace plans run roughly $7–8 (Starter), $14–17 (Standard), and $22–26 (Plus) per user per month with Gemini included; Enterprise is custom-quoted.
  • Models: Gemini 3.5 Flash launched May 19, 2026 at $1.50/$9.00 per million tokens, beating the previous Gemini 3.1 Pro on coding benchmarks at about 25% lower API cost — relevant if your team also builds on top of the model directly.
  • Advantage: Because AI is bundled rather than metered per seat, a Google Workspace-native org avoids the “who gets the AI license” administrative overhead that comes with Copilot’s add-on model.
  • Limitation: Full context grounding stays within Google Workspace apps — Docs, Sheets, Gmail, Meet, Drive. That’s the same ecosystem lock-in problem as Copilot, just on Google’s side of the fence instead of Microsoft’s, and teams needing higher usage limits still have to pay for a separate AI Expanded Access add-on.

Why Grengin is the better fit: Gemini’s bundled pricing looks attractive until you need it to reason about anything outside Workspace apps — a CRM, an internal wiki, a codebase. Grengin isn’t tied to a single vendor’s productivity suite, so the same governed chat interface can pull context from wherever your organization’s knowledge actually lives, not just from Docs and Sheets.

4. OpenWebUI

OpenWebUI is one of the most widely adopted open-source, self-hosted chat interfaces, popular with technical teams that want full control over their AI stack without paying a vendor per seat.

  • Pricing: Free and open-source. Costs come entirely from the infrastructure you run it on.
  • Strength: Full data control since nothing leaves your own servers, an active open-source community, and support for connecting multiple LLM providers.
  • Limitation: Organizational knowledge grounding (RAG), role-based access control, department-level cost tracking, and audit logging are not built in — a team has to configure, integrate, and maintain each of these separately, which usually means dedicated engineering time that most IT teams don’t have to spare.

Why Grengin is the better fit: Grengin gives you the same self-hosted control as OpenWebUI, but semantic search over organizational knowledge, granular RBAC, department budgets, and tamper-evident audit logs come working out of the box — features that would otherwise be a multi-month internal build project on top of OpenWebUI.

5. LibreChat

LibreChat is OpenWebUI’s closest open-source sibling — a flexible, developer-friendly, self-hosted chat interface with strong multi-provider support and an active contributor base.

  • Pricing: Free and open-source, self-hosted.
  • Strength: Highly customizable, plugin-friendly architecture that appeals to developer teams who want to shape the interface and integrations themselves.
  • Limitation: Like OpenWebUI, governance and organizational context are left to the deploying team. There’s no native department budgeting, no built-in semantic search over company knowledge, and RBAC has to be layered on through custom development or third-party tools.

Why Grengin is the better fit: LibreChat is a strong foundation for teams that want to build their own governance layer — but that’s exactly the work Grengin has already done. Instead of assembling RBAC, budgets, audit logs, and RAG as separate projects, Grengin ships them as one governed platform, so IT teams spend their time on rollout and adoption instead of infrastructure plumbing.

6. Grengin

Grengin sits between the vendor-hosted platforms and the bare open-source options: the data control of self-hosting, without governance and organizational context left as a do-it-yourself project.

  • Deployment options: Grengin is flexible on where it runs. Teams can self-host on their own infrastructure for full control, or deploy from cloud marketplace images on AWS or Azure for a faster setup with less operational overhead — both use the same guided setup wizard for domain, SSL, OAuth, and AI provider configuration. Teams that would rather not run the infrastructure themselves at all can opt for managed hosting, run by the Grengin team — this path isn’t self-serve and requires contacting Grengin support to set up.
  • Governance: Granular RBAC with custom roles (e.g., analytics:view, ai-platform:manage) scoped at org or department level, plus tamper-evident audit logs exportable for compliance.
  • Cost control: Department-level budgets, so AI spend doesn’t become an invisible line item buried inside a single enterprise-wide invoice.
  • Context: Built-in semantic search (RAG) over organizational knowledge and conversation history — the layer that’s missing by default in OpenWebUI and LibreChat, and locked inside a single vendor’s ecosystem with Copilot and Gemini.
  • Model flexibility: Multi-provider LLM routing across OpenAI, Anthropic, Mistral, and Gemini — swap or combine providers without changing the frontend, avoiding the vendor lock-in of Copilot, Gemini, or single-model ChatGPT deployments.
  • Tooling: MCP (Model Context Protocol) integrations with per-tool access policies, so employees get connected tools without improvising with public plugins or shadow AI workarounds.

Good fit if: you want the data control of self-hosting or the flexibility of managed cloud deployment, without rebuilding governance and organizational context from scratch.

How to Actually Choose

Don’t pick based on the demo. Test against your hardest real conversations, not your easiest FAQs. A practical evaluation checklist:

  1. Where does your team already work? Microsoft 365 → Copilot has the integration edge. Google Workspace → Gemini is effectively free. Neither, or a mixed stack → the field opens up, and vendor-agnostic platforms like Grengin start to matter more.
  2. Do you need to avoid vendor lock-in? ChatGPT Enterprise, Copilot, and Gemini each tie you to one model family. Grengin, OpenWebUI, and LibreChat let you route across providers.
  3. How much governance do you need out of the box? If you’re in a regulated industry, compare RBAC, audit logging, and data residency features — don’t assume “self-hosted” means “governed.” OpenWebUI and LibreChat leave that work to you; Grengin ships it built in.
  4. Does the platform know what your company knows? This is the gap most buyers miss. A platform that can’t ground answers in your own documents and past conversations will keep producing generic output regardless of how good the underlying model is.
  5. What’s the real per-seat cost at your scale? Add-on prices are rarely the full number — factor in base license requirements (Copilot, Gemini) or infrastructure and hosting costs (self-hosted or managed options).

FAQ

1. What’s the difference between a conversational AI platform for customer service and one for internal enterprise use? Customer-service platforms like Rasa or Kore.ai are built for external-facing dialogue — support tickets, IT helpdesk automation, voice IVR. Internal enterprise platforms like ChatGPT Enterprise, Copilot, Gemini, or Grengin are built for employees to draft, analyze, and search — a different buyer, budget, and requirement set entirely.

2. Is Microsoft 365 Copilot worth it if we don’t use much of the Microsoft ecosystem? Copilot’s main value comes from deep grounding in Microsoft Graph — emails, files, Teams, and calendar data. If your organization runs primarily on other tools, that grounding advantage shrinks significantly, and a model-agnostic platform may fit better.

3. Can open-source platforms like OpenWebUI or LibreChat replace ChatGPT Enterprise or Copilot? They can replace the chat interface itself, but not the governance and grounding features that come bundled with the paid enterprise tiers — those typically need to be added separately, which is the gap platforms like Grengin are built to close out of the box.

4. Does Grengin have to be self-hosted, or are there other deployment options? No — Grengin supports self-hosting on your own infrastructure or deployment from a cloud marketplace image on AWS or Azure, both of which are self-serve. Managed hosting, where Grengin runs the infrastructure for you, is also available but isn’t self-serve — you’ll need to contact Grengin support directly to set it up.

5. Is self-hosting an enterprise AI platform like Grengin harder to manage than a vendor-hosted option? Not necessarily for day-to-day operation — the cloud marketplace path is aimed at matching vendor-hosted setup speed while staying self-serve, and self-hosting stays available for teams that specifically don’t want data leaving their own environment. If you’d rather hand off infrastructure entirely, managed hosting is available by contacting Grengin support.

Every platform on this list can hold a conversation. The question worth asking before you sign a contract is whether it can hold a conversation that actually knows your business — that’s where Grengin, flexible governed deployment, and real organizational context come in.