Move fast, with guardrails
Give teams a sanctioned path to deploy AI while central IT sets access, models, tools and human approval policies.
- Role-based permissions
- Central prompt management
- Encrypted credentials
- Human-in-the-loop controls
The AI Operating System for higher education
University AI that makes it past the pilot.
Build, govern and deploy AI agents from one platform. Give teams approved prompts, knowledge and workflows, then deliver answers through accessible web embeds, collaboration tools and voice—with every run visible to central IT.
200+
AI agents launched
<1 week
average managed deployment
1,081 hrs
saved in seven months at one institution
✓
Real platform UIRepresentative demo data
↗
Every run traceableModels, tools, usage and outcomes
From the people who already understand higher education
Student engagementDigital transformationInstitutional AI
Proven in the real world
Explore all success stories ↗
AI outcomes from institutions like yours.
96%
of student questions answered by its Gecko chatbot after adopting ChatGPT.
Read the story ↗
1,081 hours
saved in seven months, while 63% of chatbot conversations happened out of hours.
Read the story ↗ eCampusUniversity System of Georgia 30,000 studentssupported around the clock by ChatGPT-powered Gecko chatbots.
Read the story ↗
95%+
chatbot success after integrating ChatGPT with live university website content.
Read the story ↗Results are from published Gecko chatbot case studies. Every institution and use case is different.
The CIO imperative
AI demand is everywhere.
AI demand is everywhere.
Institutional control has to catch up.
Your teams are already experimenting. The challenge is turning scattered enthusiasm into a secure, connected and measurable institutional capability.
Connect the whole institution
Ground agents in trusted university knowledge and let them work across your existing systems, channels and services.
- Websites and knowledge bases
- Existing or custom MCP servers
- APIs, webhooks and scheduled triggers
Make value visible
See what ran, what it cost, how long it took and whether it worked—across agents and workflows in one view.
- Success and failure rates
- Usage, duration and tool calls
- Run and step-level traceability
Build the value case
Turn routine demand into capacity your teams can use.
Model the operational case with your institution’s own assumptions. The calculator estimates staff capacity returned—not guaranteed budget savings.
Illustrative annual impact
Updates live
Your capacity case
- Enquiries resolved by AI
- 61,200
- Staff hours returned
- 8,160
- Capacity equivalent
- 4.95 FTE
- Indicative capacity value
- £244,800
Indicative first-year ROI
879%
Indicative payback
1.2 months
How to read this: capacity value reflects staff time that could be redirected to complex cases, proactive support or service improvement. It is not the same as a cashable saving.
Transparent method
Monthly enquiries per department × departments × 12 × addressable share × handling time × hourly cost. ROI subtracts annual investment; FTE uses 1,650 hours per year.
Conservative by design
Excludes retention, revenue, risk reduction and the value of out-of-hours service.
Ground it in evidence
Validate assumptions with service data and a bounded pilot. University of Birmingham Dubai reported 1,081 hours saved in seven months.
Your institutional AI Operating System
Put agents into production—without losing control.
From centrally managed prompts to production agents, Gecko gives technical teams and domain experts a shared place to build responsibly.
Agent & Prompt Studio
Create agents around a centrally managed library of reusable prompts. Organise templates, add dynamic variables and conditional logic, then use them consistently across agents and workflow AI calls.
Bring your first use case →Visual workflow builder
Orchestrate multi-step work with branching, parallel execution, AI calls, code, approvals, authentication and notifications.
Knowledge engine
Crawl websites, ingest institutional content, create vector embeddings and give every agent access only to the sources it needs.
Integration layer
Connect existing MCP solutions or build your own MCP servers for proprietary systems. Add managed integrations, APIs and webhooks while keeping tool access controlled.
Unified observability
Monitor agent and workflow runs together. Trace every step, model and tool call while tracking usage, duration and outcomes.
Governance by design
Tenant boundaries, roles, API tokens, approval gates and complete run histories turn policy into practical platform controls.
From request to resolution
Design the process.
Design the process.
Let agents do the work.
AI creates value when it can act inside a real process—not when it sits in another chat window. Gecko connects reasoning, knowledge, tools and people in one traceable flow.
- ✓Trigger work anywhereSchedules, webhooks, events or another agent
- ✓Keep people in controlPause for approval or identity verification
- ✓Improve with evidenceInspect every step and outcome in the run trace
Built from real workflow actions
WebhookGenerate TextLookup KnowledgeAuthenticateMCP ToolRequires ApprovalSend MessagePass to Agent
Student support triagePublished
↗
TRIGGERStudent enquiry
⋮AI
GENERATE TEXTClassify intent
⋮⌕
LOOKUP KNOWLEDGEFind approved answer
⋮✓
CONFIDENTRespond
◎
NEEDS HELPPass to agent
Workflow ready · Every step traceable
One agent, every channel
Put one governed agent wherever people ask for help.
Deploy the same trusted knowledge, tools and guardrails across digital and voice experiences—without rebuilding the agent for every channel.
Web embeds
Use floating chat, inline conversation or AI search without rebuilding the agent—or letting website styles bleed into it.
Microsoft Teams
Install agents directly into Teams so people can find answers and complete tasks without changing how they work.
Slack
Bring governed agents into Slack conversations and channels for fast, contextual help across distributed teams.
Voice
Let callers speak naturally to an agent—or have agents make outbound calls for timely, scalable engagement.
Shared knowledgeShared toolsShared guardrailsUnified observability
Start where value is clearOne platform.
One platform.
Every university team.
Build a reusable AI capability for the institution, then let each department apply it to the work that matters most.
01
Give every student a faster path to the right answer.
Ground a support agent in approved policies, triage requests automatically and route exceptions to the right human team with full context.
Explore this use case →Example workflowEnquiry → Identify intent → Search policy → Respond or escalate
- ✓ Always-on first response
- ✓ Consistent, source-grounded answers
- ✓ Human handoff for sensitive cases
02
Turn every prospective student signal into timely action.
Qualify enquiries, personalise follow-up and coordinate activity across admissions systems while keeping recruiters focused on high-value conversations.
Explore this use case →Example workflowNew lead → Enrich context → Draft follow-up → Approve → Send
- ✓ Faster response times
- ✓ Personalised engagement at scale
- ✓ Approval before outbound contact
03
Resolve routine demand before it reaches the service desk.
Connect institutional knowledge and service tools to triage requests, guide users through fixes and create enriched tickets when human support is needed.
Explore this use case →Example workflowRequest → Diagnose → Guide resolution → Verify → Escalate
- ✓ Lower repetitive workload
- ✓ Better ticket context
- ✓ Complete resolution trace
04
Give staff more time for judgement, teaching and support.
Automate information gathering, content drafting and administrative coordination while preserving expert review at every important decision.
Explore this use case →Example workflowRequest → Gather sources → Draft → Expert review → Publish
- ✓ Less administrative drag
- ✓ Approved source material
- ✓ Expert sign-off retained
05
Scale thoughtful engagement without losing the human touch.
Use trusted relationship context to prepare outreach, surface opportunities and coordinate follow-up across alumni and development teams.
Explore this use case →Example workflowSignal → Research context → Recommend action → Approve → Record
- ✓ Better-prepared conversations
- ✓ Consistent follow-through
- ✓ Controlled data access
Built on experience, not theory
We were doing higher ed AI before it became a board agenda.
Gecko already powers the moments that shape the student journey. Now we’re helping institutions turn AI from a collection of pilots into a durable, governed capability.
200+
agents already launchedwith published outcome examples
Part of the Gecko ecosystem
One partner across engagement and institutional AI.
Build on a higher education platform already supporting the student lifecycle:
AI chatbotLive chat & messagingCloud call centreForms & automationEventsCampaignsStudent portal
Explore Gecko Engage ↗
Open where it matters. Controlled where it counts.
Built to fit your architecture.
Choose how you connect, how you consume AI and how your teams work—without compromising the institutional standards IT is responsible for.
Model Context Protocol
Make proprietary systems agent-ready.
Connect any existing MCP solution in your estate, or build your own MCP server to expose approved tools from proprietary systems. Gecko discovers the available tools and lets administrators control exactly which agents can use them.
- ✓ Use existing MCP servers
- ✓ Build custom MCP connectors
- ✓ Scope tools by agent
YOUR SYSTEMProprietary service
MCPTools exposed securely
GECKOApproved agent
Bring your API key—or use ours.
Use institution-owned provider credentials when that fits your procurement and governance model, or use Gecko-managed AI access for a faster path to production.
OpenAIAnthropicAmazon Bedrock
Designed for institutional assurance.
Hosted on AWS and backed by the standards universities expect from a strategic technology partner.
SOC 2 assuranceISO 27001AWS hosted
Built for every team and every user.
A VPAT supports accessibility review, while a multilingual interface helps teams operate the platform in the languages that work for them.
Managed from first use case to go-live.
Architecture, implementation and adoption support from a team that already understands university systems, stakeholders and service expectations.
Plan your first agent →For the questions behind the question
What IT leaders want to know.
Start with the concerns that determine whether AI becomes an institutional capability or another stalled pilot.
How does Gecko help us govern AI centrally?
Central teams can control user roles, provider integrations, model access, API tokens and tool permissions. Workflows can require human approval or user authentication before sensitive actions continue, and every run retains a detailed trace.
How do teams manage and reuse prompts?
Gecko provides a central prompt library that teams can organise into folders and manage through role-based read and write permissions. Saved prompts support dynamic variables, dates and conditional logic, and can be reused by agents and workflow AI steps instead of being copied into every implementation.
Can we use our existing systems and content?
Yes. Gecko can ground agents in websites and managed knowledge, connect to providers including SharePoint, Google Drive, OneDrive, Dropbox and S3, and act through integrations, APIs, webhooks and MCP. You can connect existing MCP servers or build your own to give agents controlled access to proprietary systems.
How do the website embeds work?
Choose a floating chatbot, a minimal inline conversation or an AI search experience, then add the generated script tag to an approved website. Each interface can use tenant-specific colours, title text and imagery. Shadow DOM style isolation prevents the host website’s CSS from changing the interface, while keyboard, screen reader and reduced-motion patterns support accessibility review.
Are we locked into one AI model or commercial arrangement?
No. The platform supports multiple model ecosystems, including OpenAI, Anthropic and Amazon Bedrock. You can bring institution-owned AI API keys or use Gecko-managed access, matching each use case to the right model while IT retains oversight.
How do we prove whether an agent is working?
Start with a bounded outcome and baseline the current service. Unified observability then shows run volumes, status, duration, token usage, tool calls and errors across agents and workflows. Combine that evidence with enquiry volumes, handling time and cost data to build a value case your finance and service leaders can test.
How quickly can we get a production agent live?
With Gecko’s managed implementation, a fully operational agent is deployed in less than a week on average. We help define the use case, connect knowledge and tools, establish controls, test behaviour and support go-live.
How does Gecko meet enterprise IT requirements?
The platform is hosted on AWS with SOC 2 and ISO 27001 assurance. Gecko also provides a VPAT for accessibility review and makes the administrative interface available in multiple languages.
Where should our institution start?
Start with one bounded process where demand is high, knowledge is trusted and the outcome is measurable. Gecko can help shape that first use case, establish the guardrails and turn what works into a repeatable pattern for other teams.
Make your next pilot a path to production.
Build your AI Operating System
Build your AI Operating System
for what comes next.
Bring us one process or service bottleneck. We’ll help you define the outcome, controls and evidence needed to turn it into a governed production agent.