Which MDR Providers Add a New Integration in Days, Not Months?

Daylight is the only provider in this comparison that states it can build a net-new integration in days, through AI-written, API-first connectors. Every other provider's fastest published number covers a pre-built catalog connector, its own agent, or one named stack; none of them cover a source the provider has never connected before.

Buyers run this comparison when a tool in their stack changes and the MDR provider can no longer see it, because the new connector request often goes into a queue with no date attached. Vendor sites answer with some version of "integrated in days," but rarely say whether that claim covers this exact case.

This article sorts each provider's fastest sourced timeline by what it actually covers, checks which providers document write-back to the source tool, and separates the technical integration clock from the slower work of building usable context.

TL;DR

• The fast claims are each scoped to one thing. Expel's under-seven-minute onboarding walkthrough covers three pre-built API connectors. Huntress's 30 minutes covers its own agent, and Zscaler MDR's Microsoft Defender setup runs 4 to 6 hours to configure and confirm. None is a net-new connector.
• Days-scale claims for net-new connectors are rare. Most providers route a new source to a catalog, a separate paid services engagement, raw ingest without detection (Huntress, Arctic Wolf), or a vendor build with no days-scale commitment.
• Write-back is documented far less than it is claimed. Daylight's integrations close in the origin tool after a verdict, described at the service level without a tool-by-tool breakdown. Expel publishes one-way status-sync documentation for SentinelOne, Microsoft Defender, CrowdStrike, and Wiz, all flowing from Workbench outward only. Rapid7's Microsoft Security connector is the one clear exception we found: it documents optional, caveated bidirectional alert closure.
• Integration speed and context building run on different clocks. Expel separates hours-to-days monitoring from several additional weeks of baselining; some providers separate a one-hour technical integration from months of context building. A POC that ends at "connected" has tested the short clock only.

What "integration in days" covers, provider by provider

A custom-source test inside the POC is what separates these models, so sort providers below by what their fastest number actually covers and watch the number for the source missing from the catalog. These comparisons track operating model, not quality: the structural difference is whether a provider relies on a fixed catalog, a separate services engagement, raw ingest, or provider-built connectors.

1. Pre-built API connectors: Expel

Expel's own onboarding walkthrough connects AWS CloudTrail, CrowdStrike Falcon, and Office 365 and confirms monitoring with a generated test alert in under seven minutes, validated inside the Expel Workbench™ platform. Expel's implementation-timeline page separates several clocks: monitoring starts "within hours to days," baselining runs four to six weeks, and the page puts full value around the 60 to 90 day mark. Expel's own integrations portfolio lists the pre-built catalog that this speed depends on; it does not publish a custom-build process for a source outside that catalog.

2. Agent-bound or scoped timelines: Huntress, Zscaler MDR, eSentire, Critical Start

Huntress says Managed EDR can deploy in as little as 30 minutes with its own agent, though the same page notes onboarding can run weeks to months depending on environment complexity. Zscaler MDR's own Microsoft Defender documentation states that connecting the integration "generally takes 4-6 hours to configure and confirm data is flowing properly."

eSentire states a 14-day average to a fully deployed MDR solution. Critical Start's own endpoint MDR page states "4-6 weeks on average" for onboarding, with "total time to first value of approximately 5-10 business days." We could not find a primary, vendor-published figure for SentinelOne's MDR (Vigilance Respond) deployment timeline, so it stays out of this grouping until a sourced figure surfaces.

3. Unscoped or narrower-than-advertised claims: Arctic Wolf, Rapid7, CrowdStrike

Arctic Wolf's own supported-integrations documentation concedes it "may not have rulesets or parsing available for all sources"; the only dated deployment figure we could source for Arctic Wolf is a UK G-Cloud listing from reseller Storm Technologies stating onboarding at "30 days or less," a single, longer figure than the multiple fast timeframes sometimes quoted for the vendor.

Rapid7 publishes a customer story describing MDR onboarding as straightforward once a baseline is set, but the story does not state a "within days" figure, so we are not repeating that number here. CrowdStrike's own Falcon Complete data sheet states it is "designed to be up and running in hours (not days or weeks)" without naming the data source or environment that figure assumes.

4. Net-new sources: where the models diverge

Daylight's own MDR service page states "AI-assisted integrations in days, not the months it takes with providers," and takes requests for new sources through a form on its integrations page. Daylight is a MASS company, meaning it offers managed agentic security services for Security Operations. It starts with AI-native MDR and extends the same architecture to threat hunting, phishing response, and DLP.

Other providers also build sources themselves. Rapid7's own MDR for Enterprise announcement names a "Custom Event Source Integration" capability built to "extend visibility to proprietary, vertical-specific, or legacy technologies that standard integrations don't cover," though Rapid7 does not attach a days-scale commitment to that path. Other models include custom parsers during onboarding, paid per-integration deployment services, and detection delivery in a later release cycle. No vendor we reviewed publishes a price, a services rate, or a customer-reported timeline for custom work. The table below summarizes the groups above.

The right-hand column shows the documented path you would follow when the stack changes and the catalog does not. SentinelOne is not scored here because we could not find a vendor-published deployment timeline for its MDR offering.

Why the connector model sets the speed ceiling

How the provider collects telemetry decides whether a new source is an afternoon or a project. An API integration can often be configured in a single session, while log forwarding typically adds setup work: syslog configuration, network routing changes, or appliance deployment. Sensor and agent models buy host depth but can extend deployment time beyond pre-built API connections.

API connectors carry their own maintenance bill. In Q2 2025, Red Canary (now Zscaler MDR) rebuilt its AWS integration to ingest GuardDuty alerts via an S3 bucket and recommended that customers on the legacy version upgrade.

If the MDR runs on your SIEM, the parser is yours or theirs by contract, not by default. Expel's Managed SIEM, announced in March 2026, places its detection engineers inside the customer's own SIEM, building detection logic the customer retains ownership of. A provider running its own data lake centralizes every customer's telemetry in one place, avoiding a parser that lives inside a separate SIEM tenant per customer. Ask whether a connector built for you joins the shared catalog or stays per-customer work.

Write-back is documented far less than it is claimed

A read-only integration moves the alert into the provider's console and leaves it open in yours, so a fast integration can still hand your team a closure backlog.

Rapid7's bidirectional closure is scoped specifically to its Microsoft Security connector; InsightIDR overall and ServiceNow ticketing remain creation-only. We did not find vendor documentation showing Okta alert closure at source for any provider in this table, Daylight included.

Integration speed and context building run on different clocks

A connector going live tells you the provider can read your tool; it tells you nothing about whether the provider has business context about user roles, normal working hours, and historic behavior. In practice, getting systems wired up can take hours to days, while producing valid, denoised cases can take weeks.

Daylight's own materials break this into several distinct milestones: its onboarding comparison puts technical integration at about an hour, broader onboarding at about a week, and an initial context layer at a few additional days. Separately, full context building, in which security experts develop telemetry, organizational, and historic context to the point of full value realization, takes three to five months in Daylight's stated timeline. These are different checkpoints in the same process; ask any provider which checkpoint its headline number actually describes.

Daylight also reports reaching zero alert backlog within a three-week evaluation window. The company has not published the cohort size, starting backlog, or measurement method behind that figure, so use it as a starting point when you design your own POC test. A three-week evaluation measures early responsiveness; full onboarding and context-driven value realization run on the longer, multi-month timeline covered above.

The challenge of mapping organizational context includes accounting for environment-specific exceptions and access rules that a generic ruleset would miss. Budget the POC for the connectors and the first months of the contract for the business context.

How to decide

Use these checks to match connector claims to your environment and operating model, and run the custom-source test and the local-exception replay during the POC, before the request-for-proposal stage.

• If you run proprietary apps or niche sources, then make a custom-source test the pass/fail gate of the POC. Pick one source not on the provider's list and record elapsed time from request to first usable detection, and who did the work.
• If you intend to keep your current security stack, then ask "Do I need to buy specific security tools to work with you?" and treat a yes as an operating-model constraint. Read the licensing fine print: Zscaler MDR's Wiz integration requires an active Zscaler MDR Cloud subscription plus a Wiz Advanced Cloud License, and Microsoft's 1,500-seat minimum ties specifically to its 2026 promotional pricing on the Defender Experts Suite; confirm whether that threshold, a general purchase prerequisite, or any seat gate on individual third-party sources actually applies to your deal.
• If your team cannot maintain integrations, then get connector ownership in writing before signing: who builds, who monitors, who fixes on API or schema change, and who pays. Vendors rarely publish this language, so draft it yourself.
• If your ITSM is the system of record, then score bidirectional ticketing and source-tool closure as weighted requirements. Documented two-way ticketing was uncommon among the providers we reviewed here.
• If your environment carries many local exceptions, then weight the context test above the connector count. Replay an alert that is benign only because of your environment and check whether the provider resolves it, where that context lives, and who updates it.
• If your infrastructure is mostly on-premises, then expect less value from providers built for cloud environments; Daylight is upfront that its own model is built for the cloud.

Why provider-built connectors became the buying criterion

Provider-built connectors became the criterion because the stack now changes faster than vendor catalogs do. The three buyer paths differ by operating model and accountability: Traditional MDR, AI SOC, and AI-native MDR.

Traditional MDR was built for a perimeter-era stack of sensors, agents, and log forwarding. Adding a source means parsing, rule mapping, and often a services engagement, which creates friction when identity, cloud, SaaS, and endpoint sources change faster than a fixed catalog.

AI SOC tools invert the labor: in most cases, the buyer's internal team connects the tools, operates the platform and retains responsibility for every verdict.

Treat AI-native MDR as the standard to buy against when connector ownership matters. In this model, the provider builds API-first connectors and runs investigation and response as a managed service through an AI-native platform. A Glass Box model can also expose investigation decisions that a black-box model would hide.

Unlike AI SOC tools, MDR contracts carry service-level accountability. This model does not eliminate integration complexity: API permissions, schema changes, validation, and ongoing maintenance still need a named owner. For a new source, a provider that builds and maintains connectors itself turns the work into a request with a date instead of a queue entry.

Daylight takes new-source requests through the same form noted above, and its MDR service page carries the same days-scale connector claim covered earlier. Its platform handles detection through response for most alerts, with its security experts taking over complex or high-risk cases, and bidirectional integrations close benign alerts at the source after a verdict. Full business context building still takes months, as noted above. During the POC, ask to watch closure happen per tool in your own console and bring the source your current provider has not connected.

Frequently asked questions about switching MDR providers

How long does switching MDR providers take from start to finish?

Budget for several tracks running at once: contract offboarding with the outgoing provider, technical onboarding with the new one, and a cutover window where both can see live alerts. The timelines compared in this article cover only the technical onboarding track; contract and offboarding typically add weeks on either end that a vendor's "integration in days" claim never counts.

What happens to alerts during the cutover from one MDR provider to another?

Coverage during a provider switch comes down to a contract question: ask both providers, in writing, who owns detection and response for each source during the overlap window, and for how long. A provider that connects a source quickly still needs time to build the context that makes its verdicts reliable, so treat the technical go-live date and the date you can safely drop the outgoing provider as separate milestones.

How much does a custom MDR integration typically cost?

None of the providers compared here publish a standard rate for building a connector to a source outside their catalog. Where a path exists, it usually runs through a services engagement billed separately from the MDR subscription. Get a written quote and a delivery date during the POC.

Do I need to keep my old MDR provider running while I onboard a new one?

In most cases, yes, for any source the new provider has not yet validated. Ending the old contract the moment the new one goes technically live leaves a source still mid-onboarding unmonitored. Set the cutover date around your slowest source to onboard, and confirm the new provider has delivered a validated detection for every source before the old one is decommissioned.