The deal doesn't die in the demo. It dies in the two weeks after.

Buyers evaluating alternative datasets sign agreements with multiple vendors in the same week. Then they wait to see whose data shows up first. The first vendor to deliver gets the analyst team's full attention. The last vendor to deliver gets whatever time is left, which is usually not much.

Informal shortlists form fast. Budget decisions follow. By the time a slow vendor's trial finally arrives, the evaluation has already shaped itself around the datasets that got there first.

The problem is almost never data quality. It's delivery.

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What Actually Creates the Delay

Most alternative data vendors handle trial delivery the same way: manually, one client at a time.

A buyer signs an agreement. Sales passes the request to engineering. Engineering figures out what the buyer needs, configures access to the right storage environment, sets up permissions, issues credentials, tests the connection, and coordinates with the buyer's technical team to confirm it works.

Every step takes time. Every hand-off adds a delay. And because each client gets its own configuration built from scratch, often against a different cloud environment than the last one, there's no efficiency gained from doing it more often.

Credential management makes it worse. Vendors relying on long-running static credentials to grant data access carry an ongoing operational burden. Every time credentials need rotating or revoking, it's another round of manual work.

The result: one to four weeks for what should take less than a day.

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What Buyers Do While They Wait

They don't wait. They work with what they have.

A quant fund running a structured evaluation has a defined window. When two vendors deliver within days and three take weeks, the allocation is obvious. Fast vendors get thorough analysis. Slow vendors get a rushed review, or none at all.

Even when data does arrive, buyers face a second friction point: getting it into the right place. Most vendors provide the buyer with access to their S3 bucket, but that's rarely where the analysis actually happens. Moving data from S3 into a Snowflake environment, a Databricks workspace, or an internal data lake requires additional steps — pipeline configuration, format handling, access mapping — that fall on the buyer's own team. Compounding this, every vendor structures their data differently: directory layouts, update conventions, and file naming vary from one provider to the next, meaning the buyer's team must also figure out how to normalise and arrange that data to meet their own internal standards. It's time they hadn't budgeted for, and it pushes the real evaluation start date back further still.

That's not just an inconvenience. Buyers at quantitative funds and asset managers read delivery speed as a signal about how the vendor operates overall. Slow trial setup implies slow production support, slow data updates, slow incident response. It's not unfair inference. It's pattern recognition.

A vendor with genuinely superior data can still lose that evaluation, not because the buyer chose wrong, but because the buyer chose with the information they had, and your data wasn't part of it yet.

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Hours from Signed Agreement to Delivered Trial

Lakeshore was built by Eagle Alpha directly out of experience in the alternative data market. The core problem it solves is simple: trial delivery shouldn't need an engineering ticket.

Vendors connect their data to Lakeshore once. From there, they can personalise the data to each consumer — specifying trial or production access, coverage, and format — and share it by using a simple link, with granular access controls, MFA enforcement, and no long-running credentials to manage, delivered to whatever cloud environment the buyer uses. No new integration per client. No credential backlog. No engineering queue.

One of the vendors using Lakeshore let us know that they had delivered data to a [quant / multi-strat fund] within 48 hours. Their process went like this: Trial agreement signed → Lakeshore link shared to POC in the fund → fund self-served the onboarding to their preferred environment → Vendor received notification the data had been successfully ingested by the fund.

The vendor said it was the fastest delivered trial delivery they had ever sent. The fund had configured their preferred destination themselves — no back-and-forth over cloud account details, no unfamiliar environment to deliver to. That dataset went to the top of the funds' testing queue, ahead of vendors who were still configuring access days later.

That's not an exceptional outcome. It's what delivery looks like when it's not blocked by engineering capacity.

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Why First in the Queue Compounds

Getting into the testing queue first isn't just about speed. It's about what happens next.

When analysts start with your dataset, they build fluency in it, its structure, its coverage, its edge cases. They develop hypotheses around it. They invest time. That investment creates inertia. Vendors who arrive later aren't evaluated on neutral ground. They're evaluated against a mental model the analyst already built around the data they tested first.

There's also a more direct commercial reality at play: budget. Alternative data budget allocations are not unlimited, and funds don't hold capital indefinitely in reserve waiting for slower vendors to show up. The vendor who delivers first gets evaluated while the budget is still open. A competitor who takes a month to configure access may arrive to find the conversation has already moved on — not because the fund lost interest, but because the budget line item was filled. Speed isn't just about analyst attention. It's about being in the room before the decision is made.

A same day delivery window means your data is part of that process from the beginning. Not playing catch-up to a competitor who got there first.

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The Fix Isn't More Engineers

Hiring more engineering capacity to handle trial setup scales linearly with client volume and still produces delays. It just makes the delays slightly shorter and significantly more expensive.

The fix is removing engineering from the delivery path entirely for standard trial and onboarding workflows. When access management, cloud delivery, and security controls are handled by the platform, not configured manually per client, delivery speed stops being dependent on your engineering capacity.

Connect once. Deliver anywhere your customers choose. That's what Lakeshore does.

Speed stops being an exception you occasionally manage to pull off. It becomes the default.

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Ready to be first in the queue?

If slow trial delivery is costing you evaluations, Lakeshore was built to fix exactly that. See how alternative data vendors are cutting setup time from weeks to hours. Book a demo