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Definition

What Is a Managed Intelligence Provider (MIP)?

An MSP keeps your systems running. A Managed Intelligence Provider runs the AI agents that do work inside your business, and answers for the outcome. Here is the definition, how it compares with an MSP and an MSSP, and what changes when the intelligence runs on hardware you own or in your own Azure subscription.

A Managed Intelligence Provider (MIP) deploys, governs and runs AI agents as an ongoing managed service, and is judged on business outcomes rather than uptime or ticket counts. Pax8 coined the category in 2025. Tekscape runs a private variant: agents on hardware you own or in Microsoft Azure, grounded in a semantic model of your business, with outside frontier models used only when they are the better deal.

A glowing secure boundary around on-premises AI hardware, with one gated link out to the cloud

The definition

What a Managed Intelligence Provider is

A Managed Intelligence Provider (MIP) is a service provider that deploys, governs and runs AI agents for a business on an ongoing basis. The agents reason over the business's data, act inside its systems and are measured against agreed outcomes. The provider owns the operation of those agents, not just the infrastructure under them.

Pax8 introduced the Managed Intelligence Provider term in June 2025, in the announcement of its research report "The Agentic Inflection Point". In a later article, "The Rise of the Managed Intelligence Provider" (October 2025), Pax8 defines it this way: "A Managed Intelligence Provider is a business partner who goes beyond infrastructure support and ticket resolution. MIPs deploy and manage intelligent systems with AI agents that reason, adapt and act in real time."

Pax8 draws the line against the traditional MSP in one sentence: "Instead of software, MIPs deploy intelligence and manage outcomes." Its marketplace page adds that MIPs deliver "measurable outcomes for SMB clients, with governance, accountability, and continuous optimization built in."

Credit for the category belongs to Pax8. The rest of this page is Tekscape's view of what the model means for a buyer, and how we run it.

Comparison

MIP vs MSP vs MSSP

The three models overlap in tooling but differ in what the provider is accountable for. The last column shows Tekscape's private variant.

Managed Intelligence Provider compared with a managed service provider (MSP) and a managed security service provider (MSSP). Typical patterns, not a formal standard.
MSPMSSPManaged Intelligence Provider (MIP)Private MIP (Tekscape)
What they manageDevices, users, networks, cloud tenants and the help deskSecurity monitoring, detection, response and compliance controlsAI agents that do work inside business processesAI agents plus the hardware they run on, the semantic model they reason over and the harness around them
What you buyKeeping systems up and users productiveReduced risk and faster response to threatsWork done: processes run, questions answered, decisions supportedThe same outcomes, with your data and models kept on hardware you own or in your Azure subscription
How value is measuredUptime, ticket volume, response and resolution timesDetection and response times, audit findings, incidents containedBusiness outcomes agreed up frontAgreed outcomes plus cost predictability against a documented break-even
Pricing modelRecurring fee, usually per user or per deviceRecurring fee, usually per endpoint or per userRecurring fee tied to managed agents and outcomesRecurring managed fee, on your hardware or in Azure; other cloud usage only where routing sends it
Where AI runsInside vendor SaaS tools the MSP licenses and supportsInside the security toolsNot specified by the category definitionYour hardware or Microsoft Azure, with hybrid routing to other cloud models for work that justifies it
AccountabilityThe systems workThreats are caught and containedThe agents deliver the agreed outcome, under governanceThe agents deliver the agreed outcome, and data leaves your boundary only when a routing rule allows it

Framework

Pax8's six Plays

Pax8's Managed Intelligence Provider Playbook organizes the work into six Plays: Discover, Sell, Buy, Build, Implement and Manage. The Plays are written for providers, but they also show a buyer what a complete engagement should cover.

Discover finds the processes where an agent can change an outcome. Sell turns that into a scoped, agreed business case. Buy sources the models, tools and infrastructure. Build creates the agents and their integrations. Implement puts them into production with the people who will use them. Manage runs, monitors and improves them over time.

The Play names are Pax8's. The one-line descriptions are Tekscape's reading. In our private variant, Buy and Build include sizing hardware you own or an Azure deployment and building a semantic model of your business, and Manage covers the harness, the model routing and the ontology as a recurring service.

  1. Discover

    Find the workflows worth handing to an agent.

  2. Sell

    Agree the scope, the outcome and how it is measured.

  3. Buy

    Source the models, hardware and licenses.

  4. Build

    Design the agents, the data model and the guardrails.

  5. Implement

    Deploy, test with real work and hand over.

  6. Manage

    Run, measure and improve, month after month.

Pax8 Managed Intelligence Provider (MIP) Playbook: the six Plays. Pax8 defined the framework; the descriptions here are ours. Read the Pax8 Playbook (PDF)

Source: Pax8, The Managed Intelligence Provider Playbook. The Playbook also describes a start small, ship fast, measure, expand rhythm.

Buyer checklist

What makes a credible Managed Intelligence Provider

Anyone can call themselves a Managed Intelligence Provider. As CIT Solutions notes in its explainer, there is no independent certification body, licensing board or standard for the label. Pax8's MIP Program, launched in 2026, is a vendor-run partner program, not an independent standard. So judge a provider on evidence, not on the name.

  • Customer Zero

    Pax8's Playbook calls it Customer Zero: prove the model inside your own business first. Ask a provider which of its own operations run on agents today, and ask to see them.

    • Agents in daily use, not demos
    • The same harness and governance it will sell you

  • Governance

    Every agent needs defined permissions, human review for consequential actions and an audit trail you can read. Ask who can change an agent, and how you would know.

    • Scoped tool access and identity per agent
    • Human-in-the-loop approval where it matters
    • Logs you own

  • Measured outcomes

    Agree the outcome and its measure before the build starts, then report against it. A provider that reports activity instead of outcomes is still selling a project.

    • Baseline taken before go-live
    • Outcome reporting on a fixed cadence

Tekscape's variant

The private MIP: managed intelligence on your hardware or in Azure

Pax8's definition does not address where the models run or how they represent your business. Tekscape's variant answers both. Tekscape is a Managed Intelligence Provider (MIP) for businesses in New York and New Jersey: we deploy, govern and run AI agents on hardware you own or in Microsoft Azure, grounded in a semantic model of your business.

The stack has four managed layers. Where the models run at the bottom: hardware you own or your Microsoft Azure subscription. A business ontology and semantic model on top of your data, so agents use your terms, rules and metrics. A managed agent harness around every agent: tools, memory, guardrails, human review and audit logs. Then the agents themselves, measured against outcomes.

Why the semantic model matters: in one published benchmark by vendor-affiliated authors, using insurance data only, GPT-4 answered questions over an enterprise SQL schema correctly 16% of the time, rising to 54% over a knowledge-graph representation of the same database. It is one paper in one domain, but it points the same way as the ontology approach Palantir and Microsoft Fabric use, which we size for the mid-market.

Your hardware or Microsoft Azure

Hardware you own, typically an NVIDIA DGX Spark, or your Azure subscription on Microsoft Foundry. Sized, monitored and patched.

Data + semantic model / ontology

Your systems mapped to shared terms, rules and metrics.

Agent harness: tools, guardrails, evals, audit

What each agent may touch, what it must check, and a log of what it did.

AI agents

Task-specific agents for finance, service and operations work.

Business outcomes

Work finished and measured against the metrics you already track.

Managed by Tekscape
Cloud models (routed when cheaper) Frontier models for the hard cases, reached through the harness policy gate.
Read from the bottom up. Tekscape runs the bottom four layers; the outcomes are yours.

What the private MIP includes

  • Your hardware or Microsoft Azure

    Models run on hardware you own, typically an NVIDIA DGX Spark, or in your Microsoft Azure subscription on Microsoft Foundry. Sensitive data stays under your control, and for work that runs on your hardware your cost is a known asset plus a managed fee instead of an open-ended token bill.

  • Business ontology and semantic model

    A managed model of how your business works: clients, contracts, invoices, tickets and the rules between them. Built from what you already run, then maintained as your business changes.

  • Managed agent harness

    Agent = model + harness. We run the harness: tool access, memory, guardrails, human review, evaluation and audit logs, with 24/7 monitoring and support.

  • Hybrid routing

    Routine and sensitive work stays in your deployment, on your hardware or in Azure. Hard reasoning can go to a frontier cloud model when a routing rule allows it. In the RouteLLM benchmark (LMSYS), routing between GPT-4 and a cheaper model cut cost by over 85% on MT Bench while keeping 95% of GPT-4 quality. That was a benchmark of cloud APIs, not a customer result.

Cost, stated plainly

Local AI is not always cheaper. It is more controllable.

One independent estimate, a preprint on arXiv that has not been peer reviewed, puts on-premises break-even at a few months for small models, about 2 years for medium models and about 5 years for large models. The paper finds on-prem viable mainly at roughly 50M+ tokens per month or under strict data-residency requirements. Its cost model counts GPU cost and electricity only; staffing and maintenance are excluded.

Cloud prices also keep falling: a16z estimates API prices for equivalent capability drop about 10x per year. So we size each deployment against your volume and data rules, show the break-even with your numbers, and route the rest to the cloud. What you get is control and predictability. Savings depend on the workload.

Run your own numbers in the local vs cloud AI cost calculator.

A note on the abbreviation

MIP also means Microsoft Purview Information Protection

In the Microsoft ecosystem, MIP is the established abbreviation for Microsoft Purview Information Protection, the sensitivity-labeling technology behind the MIP SDK. If you manage a Microsoft tenant, you have likely seen it used that way.

On this site, MIP always means Managed Intelligence Provider, and we spell it out. The two are compatible: Purview sensitivity labels are one of the controls a private MIP can respect when deciding what an agent may read or send to the cloud.

FAQ

Frequently asked questions

What is a Managed Intelligence Provider?
A Managed Intelligence Provider (MIP) is a provider that deploys, governs and runs AI agents for a business as an ongoing managed service. Pax8, which coined the term in 2025, describes it as a partner that goes beyond infrastructure support and ticket resolution to deploy and manage intelligent systems with AI agents. The provider is accountable for agreed outcomes, not just for keeping systems up.
How is a Managed Intelligence Provider different from an MSP?
An MSP manages your systems; a Managed Intelligence Provider manages AI agents that do work in your business. MSP value is measured in uptime and ticket response. Managed Intelligence Provider value is measured in agreed business outcomes, with governance and continuous optimization of the agents. Some Managed Intelligence Providers, Tekscape among them, grew out of MSP work and still run the underlying IT.
Who created the Managed Intelligence Provider category?
Pax8 created it, introducing the Managed Intelligence Provider term in June 2025. Pax8 later published a Playbook with six Plays (Discover, Sell, Buy, Build, Implement, Manage) and launched a partner program for providers in 2026. Tekscape uses the term and credits Pax8 for it; our private variant, on your hardware or in Microsoft Azure, is our own.
Is there a certification for Managed Intelligence Providers?
No independent certification or standard exists for the label. CIT Solutions notes there is no certification body, licensing board or standard; Pax8's program is a vendor-run partner program. Tekscape does not claim a Pax8 designation. Judge any provider on Customer Zero proof, governance you can inspect and outcomes measured against a baseline.
Is running AI on your own hardware always cheaper than cloud AI?
No; it depends on model size, volume and data rules. One independent preprint estimates break-even at a few months for small models, about 2 years for medium models and about 5 years for large ones, and finds on-prem viable mainly at roughly 50M+ tokens per month or under strict data-residency rules. Its cost model excludes staffing. We show the break-even with your numbers and route the rest to the cloud.
Does MIP mean Microsoft Purview Information Protection?
In the Microsoft ecosystem, yes, MIP usually means Microsoft Purview Information Protection. On tekscape.ai, MIP always means Managed Intelligence Provider, and we spell it out on first use. The two work together: Purview sensitivity labels can be one of the rules that decides what an agent may read or route to a cloud model.

Sources

  1. Pax8: The Rise of the Managed Intelligence ProviderSource of the quoted Managed Intelligence Provider definition and the MSP contrast.
  2. Pax8: The Agentic Inflection Point (2025 research report announcement)Pax8 introduced the Managed Intelligence Provider term in June 2025.
  3. Pax8 Marketplace: AIMarketplace definition: measurable outcomes, governance, accountability, continuous optimization.
  4. Pax8: The Managed Intelligence Provider Playbook (PDF)Six Plays; Customer Zero; start small, ship fast, measure, expand.
  5. GlobeNewswire: Pax8 Launches Managed Intelligence SolutionsPax8 MIP Program launch, 2026.
  6. CIT Solutions: What Is a Managed Intelligence Provider?No independent certification body, licensing board or standard exists.
  7. Microsoft Learn: MIP SDK metadata conceptsMIP as Microsoft Purview Information Protection.
  8. arXiv preprint: on-premises vs API LLM cost break-evenPreprint, not peer reviewed; cost model counts GPU cost and electricity only.
  9. LMSYS: RouteLLMBenchmark of routing between API models, not a customer result.
  10. a16z: LLMflationAPI prices for equivalent capability fall about 10x per year.
  11. arXiv: knowledge graphs and LLM question answering over enterprise SQLBenchmark by vendor-affiliated authors, insurance domain only.
  12. Microsoft Learn: Fabric IQ overviewOntology approach referenced as an analogy; Fabric IQ ontology is in preview. No partnership implied.
  13. Palantir: Ontology systemOntology approach referenced as an analogy. No partnership implied.

See what a private Managed Intelligence Provider would run for you

Tell us one process you want an agent to own. We will map it to your hardware or Microsoft Azure, the semantic model it needs and an honest break-even against the cloud.

Talk to Tekscape