Enterprise AI is fragmented across too many systems
AI now runs across copilots, assistants, APIs, agents, developer tools, and internal systems. Each one has its own admin console, its own billing, and its own definition of an active user.
Midgentic creates a unified intelligence layer across that environment.
- What AI are we using?
- Who is actually using it?
- What does it cost?
- Is adoption improving?
- Where are we wasting money?
- What business value is it producing?
- What needs governance attention?
Five capabilities in one platform
Connect
Connect your enterprise AI ecosystem through automated connectors, manual entry, and CSV imports.
Monitor
Track usage, adoption, spend, and provider health as your AI footprint changes.
Govern
Surface portfolio health, oversight signals, and the areas that need attention.
Measure
Connect AI investment to business value and ROI, with estimated and measured value kept separate.
Optimize
Find underutilization, waste, adoption gaps, and opportunities to improve AI investment.
From fragmented AI data to executive intelligence
Connect your AI ecosystem
Connect supported enterprise AI platforms directly and bring in additional AI data through manual or CSV imports.
Unify fragmented AI data
Midgentic brings adoption, usage, spend, governance, license, and business-value signals into a common intelligence layer.
Turn data into executive intelligence
Understand what is being used, what it costs, where adoption is weak, what needs governance attention, and where AI is producing measurable value.
Connect the AI platforms you use today
Midgentic supports enterprise AI environments through a combination of automated connectors, manual data imports, and expanding integration coverage. Every metric is labeled with where the data came from, so an automated sync is never confused with a manual import.
Automated connectors
BetaLive connectors authenticating directly with the vendor. Catalogued as beta today, which means behavior may still change.
- Microsoft 365 Copilot
- GitHub Copilot
- Google Workspace with Gemini
- Claude Enterprise
- OpenAI API Platform
- Anthropic API Platform
Manual and CSV import
Available todayAnything without an automated connector can still be tracked: licenses, usage exports, spend, and outcomes are entered or imported and treated as first-class portfolio data.
- ChatGPT Enterprise
- Additional enterprise AI tools through manual and CSV workflows
- Internal AI applications and custom usage sources
Built for the enterprise AI ecosystem
Midgentic is designed to provide a common intelligence layer across the growing enterprise AI landscape. Track copilots, assistants, developer AI, agents, collaboration tools, API platforms, infrastructure, and internal AI data as your environment evolves.
AI Assistants
Enterprise copilots and assistants used across the business.
- Microsoft 365 Copilot
- ChatGPT Enterprise
- Claude Enterprise
- Google Workspace with Gemini
- Perplexity Enterprise
- Glean
AI Development
Developer AI and coding assistants used by engineering teams.
- GitHub Copilot
- Cursor
- Windsurf
- Replit
- Codeium
Enterprise AI Agents
Agents embedded in the business applications you already run.
- Salesforce Agentforce
- ServiceNow AI Agents
- SAP Joule
- Workday AI
- HubSpot Breeze
Collaboration AI
AI inside the collaboration and productivity layer.
- Microsoft Teams with Copilot
- Slack AI
- Zoom AI Companion
- Notion AI
- Atlassian Rovo
AI Infrastructure and Data
API platforms and AI infrastructure behind internal builds.
- OpenAI API Platform
- Anthropic API Platform
- Google Vertex AI
- AWS Bedrock
- Microsoft Azure AI
- Databricks
- Snowflake
Bring your own data
Anything outside a supported connector still belongs in the portfolio.
- CSV usage exports
- Internal AI applications
- Contract and license data
- Business outcomes
- Custom usage sources
Category examples describe the enterprise AI landscape Midgentic is built to model. They are not a claim of automated integration with every provider listed. Coverage today is set out in current connectivity, and integration coverage expands over time.
See who is actually using AI
License counts tell you what was bought. Midgentic shows what is being used, and whether that is improving month over month.
- Active usage by provider
- Adoption trends over time
- Utilization against licensed seats
- Inactive and dormant users
- Department visibility where the source data supports it
- Application and feature usage where available
Understand what AI actually costs
Contracted licenses and consumption-based API usage sit in one place, in the currency each contract is billed in.
- Contracted license spend
- API consumption spend
- Spend by provider
- Inactive license exposure
- Utilization analysis
- Optimization opportunities
Know which parts of the portfolio need attention
Governance in Midgentic means portfolio oversight: whether your connectors are healthy, whether your data is complete, and whether licensed capacity is being used.
- Connector health and data freshness
- Data coverage across the portfolio
- Usage oversight
- License utilization
- Governance signals
- Incomplete setup detection
- Connector health
- Authentication, sync status, and failures by provider
- Data freshness
- How current each provider's data is
- Usage oversight
- Where activity is concentrated and where it has stalled
- License utilization
- Licensed capacity against actual use
- Portfolio coverage
- Which parts of the AI estate are still unmeasured
- Evidence-backed signals
- Every signal traced to the data behind it
Governance here means portfolio oversight. Midgentic does not inspect prompts or content and is not a DLP, policy-enforcement, or AI safety tool — see the security and data access documentation for the full scope.
Connect AI investment to business value
Midgentic keeps estimated value and measured value clearly separated, so an assumption is never presented to your board as a result.
- AI investment by provider
- Estimated value from documented assumptions
- Measured outcomes you enter or import
- AI ROI across the portfolio
- Cost per active user
- Executive reporting
Recommendations backed by your own data
Midgentic reviews the underlying data and surfaces what changed, why it matters, and the evidence behind it.
- Underused licenses
- Weak or declining adoption
- Rising API spend
- Incomplete AI coverage
- Optimization opportunities
From six admin consoles to one executive view
Most AI reporting today is assembled by hand from separate vendor dashboards and invoices. Midgentic produces a consistent executive view of adoption, spend, governance, and value, with the source of each number labeled.
CIOs, CFOs, and AI leaders can take the same view into a steering committee without rebuilding it each quarter.
The leaders accountable for AI investment
CIO and CTO
Understand AI adoption, deployment, and portfolio performance.
CFO
Understand AI spend, waste, value, and ROI.
AI transformation leaders
Measure adoption and identify where AI programs need attention.
IT and governance leaders
Monitor connectivity, portfolio coverage, utilization, and governance signals.
Start with a guided Customer Pilot
Launch a guided 60-day Customer Pilot to connect your first AI systems, establish baseline visibility, and produce an executive-ready readout.
No credit card required. Guided setup included.
- Days 1 to 14BaselineConnect your first AI systems and establish a starting point.
- Days 15 to 30DiscoverReview adoption, spend, and portfolio coverage.
- Days 31 to 45MeasureAdd cost and value inputs, then track ROI.
- Days 46 to 60Prove and expandProduce an executive readout and plan the next step.
You control access
Connections are authorized by your administrators and can be revoked at any time.
No prompt or content collection
Supported adoption analytics are built from provider administrative reporting.
Vendor neutral
Midgentic reports across providers without favoring any single AI vendor.