AirMDR vs TENEX: Which MDR Model Fits?

AirMDR and TENEX both promise artificial intelligence (AI) native managed detection and response (MDR). Managed detection and response is the outsourced service in which a provider monitors a customer's security telemetry, investigates the alerts it produces, and drives containment on the customer's behalf. AirMDR vs TENEX is a choice between a broad-stack managed investigator aimed at lean teams and managed security service providers (MSSPs), and a services-heavy security operator anchored in Google SecOps and Microsoft Sentinel.

There is no universal winner. AirMDR stresses alert coverage across the stack, AI-led investigation, and human review of critical cases (AirMDR). TENEX offers security information and event management (SIEM) optimization, customer-owned Agentic Overwatch, and provider-owned Agentic MDR on hyperscaler security platforms (TENEX).

The two companies also sit at very different altitudes. AirMDR's $15.5 million seed round was independently reported by SecurityWeek. TENEX's $250 million Series B, at a valuation above $1 billion, was independently reported by Bloomberg (SecurityWeek, Bloomberg). That gap shapes roadmap speed, staffing, and account coverage. It says nothing about which provider investigates your alerts better.

Key takeaways

• AirMDR sells one managed investigation workflow across a broad stack with more than 240 reported integrations; TENEX runs natively on Google SecOps and Microsoft Sentinel with more than 300 reported connectors (AirMDR, TENEX).
• TENEX splits ownership into three tiers: Optimize for SIEM implementation, Agentic Overwatch where the customer keeps the queue, and Agentic MDR where TENEX owns the 24/7 managed outcome.
• AirMDR raised a $15.5 million seed round while TENEX raised a $250 million Series B above a $1 billion valuation, so the two companies operate at very different scale (SecurityWeek, Bloomberg).
• Neither AirMDR nor TENEX publishes normalized pricing, so ask for quotes split by data volume, alerts, protected assets, integration work, human coverage, and response authority.
• For an MSSP, AirMDR's managed offer can overlap the MSSP's own MDR service, so customer ownership and incident communication belong in the contract, not the demo.

The right shortlist follows five questions: what fits your stack, how deep the automation goes, where humans enter, who may act, and whether the commercial evidence supports the pitch. Underneath sits a maturity decision. A small security team may value broad integration and a provider-operated workflow more than platform control. A large enterprise may prefer to keep its hyperscaler SIEM, response process, and internal authority while adding engineering and overnight coverage. An MSSP has a third concern: whether the provider strengthens its service or competes for the account. Price those obligations, not the number of alerts investigated.

What Each Provider Is Selling

The quickest comparison is not a feature grid. It is a map of who operates the service and who owns the outcome, which is what makes managed detection and response one of five business models in AI IT and security services.

AirMDR: one managed investigation workflow

AirMDR documents a sequence that ingests an alert, runs quick checks, selects or generates an investigation playbook, gathers evidence, records a decision, and feeds the result back into later work (AirMDR documentation). Its virtual analyst performs first response, while human experts supervise, review critical alerts, and escalate exceptions (AirMDR).

The center of gravity is managed MDR. AirMDR also promotes the platform to enterprise security operations centers (SOCs) and MSSPs, but the proposition begins with continuous investigation capacity rather than a SIEM transformation project.

TENEX: three ownership levels

TENEX exposes a wider operating continuum. Optimize covers SIEM implementation and tuning. Agentic Overwatch puts AI-led triage, investigation, hunting, and response around a queue the customer still owns. Agentic MDR transfers the 24/7 managed outcome to TENEX (TENEX).

AirMDR is the cleaner proposition. TENEX gives a buyer more ways to divide the work, and that changes procurement. AirMDR can be assessed as a managed investigation service layered over the tools already in place. TENEX may begin earlier, with SIEM design and optimization, then remain through co-managed or fully managed operation. One reduces the burden of running the current stack. The other reshapes the stack before operating it.

Neither model is inherently better. Write down the operating gap first, then select the tier that fills it without duplicating an incumbent team.

1. Existing-Stack Compatibility

The most expensive MDR feature is the connector that does not work when an incident arrives. Test compatibility against the systems that generate your real alerts, not a logo wall.

AirMDR takes the broad-stack route

AirMDR says it covers endpoint, identity, email, cloud, software as a service (SaaS), and network detections. It reports more than 240 out-of-the-box integrations and says custom integrations can be delivered in two to four weeks. Those numbers and delivery times are company-reported, not independently verified (AirMDR).

Its documented workflow begins with alert ingest rather than a requirement to replace the SIEM. That can suit a lean team with several existing controls or an MSSP serving customers with uneven stacks (AirMDR documentation). The diligence question is whether each connector supplies enough context for a supported conclusion, not merely whether it creates a case.

TENEX starts with the hyperscaler

TENEX says Agentic SecOps runs natively on Google SecOps and Microsoft Sentinel and supports more than 300 connectors, another first-party count (TENEX). Its model improves and operates an existing hyperscaler security stack instead of abstracting away the SIEM.

That is attractive if you have already standardized on Google or Microsoft. It is less obvious if your SOC depends on another SIEM or you want a provider-neutral layer. TENEX's Optimize service may reduce implementation debt, but it also makes TENEX part of the architecture rather than a detachable alert service.

For both providers, request a source-by-source matrix covering telemetry read, write-back, retention, residency, rate limits, and failure handling. Then run a historical replay. A connector that enriches a common endpoint alert may still fail on identity context, custom SaaS logs, or a regional data boundary.

Integration depth also affects the service margin. A standard connector spreads engineering cost across customers. A bespoke parser, unusual authentication flow, or one-off response action turns onboarding into project work. AirMDR's custom-integration window and TENEX's optimization layer both signal that integration labor remains part of delivery (AirMDR, TENEX).

Ask each provider to price three states: your stack unchanged, your stack standardized, and the expected state after twelve months. The cheapest first-year quote can become the most expensive model if every new data source triggers custom work, or if the provider requires a broader platform migration.

2. Automation and Investigation Depth

An automation percentage can rise because the agent got better or because the provider narrowed what counts as an investigation. The only fair AI-native MDR comparison uses the same alerts and the same standard of evidence.

AirMDR makes the workflow visible

AirMDR's public documentation describes quick checks, playbook selection, agentic investigation, case management, and escalation (AirMDR documentation). A buyer can inspect where an agent chooses a method, where it gathers evidence, and where a human enters.

The company advertises alert-triage and investigation-time improvements, but the reviewed independent coverage corroborates its funding rather than auditing those operating metrics. Treat the percentages as first-party claims (SecurityWeek).

One outside test does exist. A reviewer on the MSP GLOBAL channel, which covers managed service providers (MSPs), ran AirMDR's free tier against its marketing claims and found real value in Tier 1 triage and evidence documentation, while flagging hallucination risk, dependence on clean telemetry, and the need for human approval gates before scaling (video review). One reviewer's test is not a benchmark, and the reviewer's own advice was to validate every vendor number in your own environment.

TENEX connects automation to an operating tier

TENEX positions its agents across triage, investigation, hunting, and response, with sub-minute and coverage claims on its own materials (TENEX). Those claims are not directly comparable with AirMDR's because the baselines, alert mixes, escalation thresholds, and units differ.

The more useful distinction is ownership. Under Overwatch, the customer still owns the queue. Under Agentic MDR, TENEX owns the managed outcome. The same agentic capability can be a productivity layer in one contract and part of a transferred service obligation in another.

Test both on the same alert set

Build one evaluation set from representative low, medium, and high-severity alerts. Include missing telemetry, duplicate alerts, legitimate administrator activity, and cases requiring business context. Score supported verdicts, missed evidence, false negatives found in review, escalations, human minutes, and response delay. Do not let either vendor substitute closed-alert volume for investigation quality.

Then test learning. Feed the same class of alert back after an analyst correction and inspect whether the next case improves, whether the change is visible, and whether it applies only to your tenant. AirMDR documents a feedback loop in its investigation process (AirMDR documentation). TENEX describes agentic work across triage, investigation, hunting, and response, but the public evidence does not provide a normalized learning benchmark (TENEX).

The goal is not maximum autonomy. It is the lowest cost per defensible decision at an acceptable miss rate. A provider that escalates more often may be the better buy if the escalations are the cases where context genuinely matters.

3. Human Backstop and Service Design

The surprising part of AI-native MDR is how much the remaining human work matters. As routine collection gets automated, the unresolved cases become more ambiguous and more consequential.

AirMDR uses supervision and exceptions

AirMDR positions the virtual analyst as the first responder and its experts as supervisors who review critical alerts and handle escalation (AirMDR). That can give a mid-market company continuous coverage without building a full internal SOC.

Ask how supervisors are assigned, whether the same analyst learns your environment, and what triggers manual review. A model built around exceptions scales well when exceptions fall. It can also become a hidden services business when poor telemetry or unusual customer environments keep the exception rate high.

TENEX foregrounds defenders and engineers

TENEX places named analysts and forward-deployed engineers at the center of delivery, alongside its agents (TENEX). A forward-deployed engineer is a provider employee embedded with one customer to build and tune the integrations, detections, and workflows that generic delivery cannot cover. That signals a services-heavy model, which may create better continuity during tuning, architecture changes, and major incidents, but can carry more labor than a narrower managed investigator.

The funding announcement reinforces that design. TENEX said its $250 million Series B would scale human defenders and engineering teams as well as international expansion (TENEX). Capital going into people is not a flaw. It tells you that skilled delivery remains part of the product.

Continuity is the part that breaks

For both providers, ask where staff sit, how coverage hands off between shifts, who owns your account during an incident, and how many customers each human team covers. Then request turnover, escalation, and quality-review data. The AI layer may perform most routine steps. Trust rests on the person who appears when the routine ends.

Turnover is not a theoretical risk here. An analyst two months into a first security operations job posted on r/cybersecurity about constant anxiety and being unable to switch off after shifts, drawing 79 mostly sympathetic replies that treated burnout as normal for the role (r/cybersecurity thread). That is sentiment, not a turnover statistic. It is also the labor condition both AirMDR and TENEX sell against, and it decides whether the supervisor who learned your environment in month one is still on your account in month twelve.

Continuity deserves its own test. Give the provider a scenario that starts as a routine alert and turns business-critical once new evidence appears, then watch whether the same context travels from agent to supervisor, across a shift change, and into customer communication. Every handoff is a place where evidence gets dropped.

Both staffing models carry an economic tell. Measure AirMDR by exceptions per customer and supervisor capacity, TENEX by how much engineering work becomes reusable across accounts, and both by whether customer growth requires proportional hiring.

4. Response Authority, Transparency, and Service-Level Ownership

“Managed response” is dangerously vague until the contract names who may isolate a device, disable an account, or interrupt a production service. That naming also settles whether you are buying software or a managed contract.

Translate AirMDR's escalation into permissions

AirMDR's workflow produces documented decisions and cases, with critical alerts reviewed and escalated by experts (AirMDR documentation, AirMDR). That establishes visibility and a human backstop. Public materials do not disclose a normalized response matrix, liability allocation, or standard service-level agreement (SLA).

Ask which actions AirMDR can take automatically, which require customer approval, how long the approval window lasts, and what happens when the customer is unavailable. Require the evidence, agent conclusion, human review, approval, and action to remain in one case record.

TENEX makes ownership tier-dependent

TENEX draws a clearer line between Agentic Overwatch, where the customer owns the queue, and Agentic MDR, where TENEX owns a 24/7 managed outcome with contractual service objectives (TENEX). The distinction is useful, but the public page does not supply the complete contract or standard remedies.

The buyer must still define containment authority, notification paths, customer dependencies, exclusions, and the meaning of a completed investigation. Under Optimize, responsibility is shared during implementation. Under Overwatch, the customer remains the operator. Under MDR, TENEX assumes more of the operational burden.

Write the response matrix before the contract

Give both vendors the same written response matrix. List actions from evidence gathering through account disablement and host isolation. Assign recommendation, approval, execution, communication, and liability for each. If a provider cannot map its service to that table, the SLA language is not yet operational.

Transparency should survive disagreement. Ask whether your analyst can see the evidence queried, the reasoning path, the alternatives considered, and the human changes made before closure, then ask how long that record lives and whether it exports if you change providers.

Set measurable service objectives around decisions, not only acknowledgements. A fast “alert received” message has little value if evidence gathering stalls. Track time to first supported verdict, time to human escalation, time waiting on customer approval, and time to executed response. Separate provider time from customer delay so neither side can hide behind one blended clock.

Finally, test an unauthorized action. The provider should show that the agent cannot cross the permission boundary, that the attempt is logged, and that escalation reaches the right person. Response authority is credible when the system fails closed and the record makes the failure explainable.

5. Buyer Fit, Channel, Pricing, and Evidence

If the technical score is close, buy the operating model that matches your distribution and economics.

AirMDR fits lean teams and mixed estates

AirMDR targets mid-market organizations, enterprise SOCs, and MSSPs seeking investigation capacity across existing controls (AirMDR). MSSP Alert described the company's funding and the intended benefit to service providers, but AirMDR's managed offer can also overlap with an MSSP's own customer-facing MDR (MSSP Alert). Clarify who owns the customer, incident communication, and services margin.

TENEX fits hyperscaler-centered enterprises

TENEX is better aligned with enterprises already committed to Google SecOps or Microsoft Sentinel and wanting implementation, co-management, or a full managed outcome (TENEX). Bloomberg independently reported its $250 million Series B, valuation above $1 billion, and partnerships with Google, Microsoft, and Amazon Web Services (AWS) (Bloomberg). Funding at that distance from AirMDR's independently reported $15.5 million seed round indicates different scale and capital strategy, not better detection (SecurityWeek).

Pricing is where this category is least honest

Neither company publishes normalized pricing. Request cost by data volume, protected identity or endpoint, alert volume, investigation, connector work, onboarding, human coverage, and response tier. TENEX reported $18 million of revenue after three quarters in market, but that remains a company-reported performance claim rather than independently verified unit economics (TENEX).

Pricing opacity is the loudest complaint in practitioner discussion of this category. An AI SOC is a security operations center where agents, not analysts, do the routine triage and investigation work. Scott Ponte, head of security operations at Robinhood, wrote after Black Hat that he sees little real differentiation between AI SOC vendors beyond interface polish, and that the category is quietly reintroducing pay-per-alert, pay-as-you-ingest pricing under a new label (LinkedIn post). One buyer's read is not a market survey, but it names the right diligence question: what does your bill do when alert volume doubles?

For an MSSP, channel conflict is as important as price. Ask whether the provider appears in front of your customer, who sends incident communications, whether your brand remains primary, and whether a direct sales team can approach the account. A low platform rate does not compensate for losing the services relationship.

For an enterprise, compare total operating cost. Include internal analysts retained, SIEM administration, integration work, incident surge support, and the management time needed to govern the provider. TENEX's three tiers make that comparison explicit. AirMDR needs the same cost split between platform, managed work, and customer responsibilities.

Evidence maturity remains limited on outcomes, and the same gap runs through the wider AI SOC vendor comparison. Independent reporting corroborates both funding events, not detection quality or gross margin. Ask for references with a similar stack and alert mix, and for cohort data showing deployment time, intervention rate, retention, and quality over time. A provider that will only show aggregate alerts processed has told you nothing about what the service costs to deliver.

The Bottom Line

Shortlist AirMDR when broad integration, a documented investigation workflow, and managed coverage for a lean team lead the decision. It is also worth testing for an MSSP that wants more investigation capacity, provided the contract protects customer ownership and service margin (AirMDR).

Shortlist TENEX when Google SecOps or Microsoft Sentinel is already the center of the stack and you want a clear path from optimization to co-managed Overwatch or a TENEX-owned MDR outcome (TENEX).

Do not choose from vendor automation percentages. Give both providers the same alert replay, response matrix, and cost template, scored on one instrument such as this vendor scorecard template. Measure supported verdicts, false negatives found in review, human work, deployment burden, and time to an authorized action. The winner is the provider that improves those measures in your environment while making accountability easier to explain.

My practical split: AirMDR is the first call for a mixed estate and a small team that wants a managed investigator. TENEX is the first call for a hyperscaler-centered enterprise that wants engineering depth and a choice over outcome ownership. Run the proof of value before negotiating the long contract, because the public evidence cannot settle detection quality or delivery cost.

For related analysis, see AI SOC economics and AI pricing models for MSPs.

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