Scattered AI usage
Teams create separate accounts and move between tools with inconsistent policies and support.
Private AI workspace for your company
Private enterprise AI chat for every employee.
Deploy a company-branded chat workspace connected to approved models from AWS Bedrock and other enterprise providers. Domain-restricted access and a familiar interface support employee adoption.
Approved models onlyCompany-domain sign-inGyde-managed rollout
◆Auto⌄
GYDE
How can I help your team?
Use an approved model directly or let Auto choose based on the task.
Ask anything or type / for team prompts
Company accessApproved providersManaged by Gyde
The operating problem
Company-approved AI access for employees.
Employees are already finding ways to use generative AI. A private workspace gives them a supported path while the business defines who can sign in, which models appear, and how the service is operated.
Uncontrolled model choice
Employees cannot easily tell which providers, models, or use cases the business has approved.
Missing service ownership
Employees need identity, a supported user experience, rollout guidance, and a named service owner alongside the model API.
Solution architecture
Identity, model access, and inference in one deployment.
The workspace separates the employee experience from provider selection. Identity, model availability, and routing are configured around your approvals; model traffic then goes to the enterprise endpoints selected for the deployment.
Google WorkspaceCompany-domain allowlist
→
Private AI ChatLibreChat-based experience
→
Model policyCatalog, routing, access
→
Approved providersAWS Bedrock or selected endpoints
iProvider retention, regional processing, and model terms follow the endpoints selected by your organization and are documented during solution design.
What employees and owners get
A useful workspace with visible boundaries.
Approved model catalog
Expose only the model endpoints the organization has reviewed. Add clear descriptions so employees can choose intentionally.
Automatic model selection
Offer an Auto experience that can route a task to an appropriate approved model using defined quality, speed, and cost policies.
Domain-restricted access
Use Google Workspace sign-in and allow only users from the company domain to enter the workspace.
Projects and team prompts
Projects, saved context, and shared prompt patterns provide a consistent workspace for recurring team tasks.
Company-branded experience
Deliver the workspace on a dedicated domain with your identity, onboarding copy, model guidance, and support path.
Defined service operations
Assign model updates, access changes, usage support, evaluation, and incident responsibilities before broad rollout.
Implementation path
Pilot with one cohort, then expand against measured thresholds.
A successful rollout defines identity, model access, policy, support, and operational ownership for the employee workspace.
1
Discover
Set the boundary
Confirm user groups, approved providers, data constraints, priority use cases, and measures for a safe launch.
2
Configure
Build the workspace
Brand the experience, connect identity, configure the model catalog, and establish routing and access rules.
3
Pilot
Launch with one cohort
Onboard a controlled group, observe task patterns, test model guidance, and resolve policy or support gaps.
4
Operate
Expand against measured thresholds
Broaden access with a named owner, model-change process, adoption metrics, and a documented support runbook.
Control model
Four boundaries make the workspace governable.
Each boundary is configured for the deployment and documented before the pilot cohort starts.
Identity boundary
Google Workspace authentication with a company-domain restriction and controlled user onboarding.
Provider boundary
Only approved AWS Bedrock models or other reviewed provider endpoints are made available.
Experience boundary
Model descriptions, default choices, team prompts, and acceptable-use guidance are visible inside the product.
Operating boundary
Access changes, model updates, evaluation, support, and escalation have named owners and a runbook.
Where teams begin
A shared workspace for approved team use cases.
Early use cases should be valuable, easy to review, and compatible with the information boundaries agreed for the pilot.
Engineering
- ↳Explain and review code
- ↳Draft tests and documentation
- ↳Compare technical approaches
Sales & Marketing
- ↳Research and summarise accounts
- ↳Draft outreach and briefs
- ↳Adapt approved messaging
Operations
- ↳Summarise long documents
- ↳Structure recurring analysis
- ↳Create first-pass process content
People & Enablement
- ↳Develop learning material
- ↳Create role-based guides
- ↳Support internal knowledge work
Used inside Gyde
We run our own deployment at chat.gyde.ai.
Gyde employees sign in with Google, work across an approved model catalog, and can use automatic model selection for everyday tasks. The customer offering starts from this operating experience and is configured for each organization.
GGYDE
Welcome to Gyde AIContinue with Google
View the Gyde sign-in ↗
Questions
Before we design the workspace.
Is this a replacement for individual public AI accounts?
It provides a supported internal alternative: one workspace, one identity boundary, and a model catalog selected by the business. Whether public tools are restricted remains an organizational policy decision.
Which models can employees use?
The catalog is deployment-specific. It can use models exposed through AWS Bedrock and other enterprise provider endpoints that your business has approved.
Can access be limited to our company domain?
Yes. Google Workspace sign-in can be configured with a domain allowlist so only users from the approved company domain can enter.
Is the workspace based on LibreChat?
Yes. The current Gyde deployment uses a customised LibreChat-based foundation. Gyde handles solution design, configuration, identity, provider integration, branding, rollout, service ownership, and support procedures.
Where does prompt data travel?
The data path depends on the deployment and approved provider endpoints. During design, we document the architecture, provider terms, retention settings, and regional choices.
Private AI, designed for adoption
Provide employees with a company-approved AI workspace.
The first rollout covers one employee cohort, a controlled model catalog, and documented provider, identity, support, and access requirements.
Design your workspace↗