How to Reduce eDiscovery Costs for Your Firm

Document review eats more than 80% of the total litigation spend. That’s the American Bar Association’s own number, and it hasn’t really budged even as data volumes have exploded over the past decade. So when managing attorneys start looking for places to trim eDiscovery costs, review is usually where their eyes land first.

Here’s the part that surprises people: cutting review time badly is easy, and it’s also the fastest way to blow a matter’s defensibility. Cutting it well takes work earlier in the process, before the data has piled up and the clock is already running. That’s what this actually comes down to.

Filter the Data Before You Ever Get to Review

Want to move the needle on eDiscovery costs? Stop looking at the review rate and start looking at what's landing in front of reviewers in the first place. A solid pass to filter and narrow the data, removing duplicates, stripping out system files, limiting the date range, narrowing custodians, and excluding irrelevant email domains, can meaningfully shrink a raw data set before anyone opens a single document. Deduplication alone, just removing exact and near-duplicate files, is often one of the biggest single contributors to that reduction.

Why does this matter so much? Because review cost tracks document count almost one-to-one. Shrink the data set, and you're not just saving review hours. Hosting costs drop. Quality control time drops. Every reviewer looks at fewer documents, which means fewer chances for something to slip through or get miscoded.

The tricky part is doing this in a way that holds up in court. A structured early case assessment does more than trim the data down. It gives you a paper trail for why certain data got excluded, plus early visibility into custodians, document types, and case strength before you commit to a full review budget.

Let TAR and CAL Do the Sorting

Technology-assisted review isn't the new thing anymore. TAR 2.0, built around Continuous Active Learning, is court-accepted and has been for years, and it's become one of the standard tools firms reach for when eDiscovery costs start creeping. Firms that adopt a real CAL workflow typically see a meaningful drop in the number of documents that require human review.

How it works, in plain terms: instead of a reviewer grinding through documents in whatever order they landed, CAL keeps reshuffling the unreviewed pile based on what reviewers have already coded, so the most-likely-relevant stuff keeps floating to the top. Reviewers spend their hours on documents that matter instead of working a static queue from front to back.

If your firm is still running keyword searches in a linear review, switching to a managed eDiscovery workflow built around CAL is probably the single biggest lever you haven't pulled yet. You don't need a new review team. You need a smarter order for the one you've got.

Be Honest About Outsourcing vs. In-House

There’s no universal answer here; it depends on matter size, timeline, and how predictable your caseload is.

In-house review pencils out when your firm handles a steady stream of matters and already has reviewers who know the platform inside and out. The fixed cost of keeping that capability around gets spread thin enough across enough cases to be worth it.

Outsourcing to a digital forensics service or a managed review vendor tends to win on the big, messy, unpredictable matters, especially when you need surge capacity you don’t keep on staff year-round, or the data itself is outside what your team normally handles. On paper, an outsourced engagement can look pricier than in-house billable hours. Factor in training time, licensing, QC overhead, and the associates you’d otherwise pull off other work, and it often comes out ahead.

For most firms, the real answer is a mix: keep the predictable, lower-complexity work in-house, and hand off the big or technically hairy matters to a managed ediscovery partner who can flex up without your firm carrying that overhead permanently. Firms that lean on e-discovery managed services specifically for surge capacity often find that’s the difference between hitting a production deadline and missing one entirely.

Pick a Platform That Doesn’t Nickel-and-Dime You

This is where a lot of firms bleed money without noticing. Legacy per-GB pricing bills separately for processing, hosting, review, and production, then tacks on fees for AI-assisted review, analytics, or even pulling your own data back out at the end. A hybrid model, mixing per-GB charges with per-user licenses and feature add-ons, is about the hardest thing to budget against, because the final invoice depends on variables nobody can pin down at the start of a matter.

An end-to-end ediscovery platform that folds collection, processing, review, and production into one predictable structure, ideally with AI-assisted review built in rather than billed on top, gives litigation support teams something they can actually plan a budget around instead of chasing a moving target. Before signing with any vendor, make them walk you through what happens to the cost at every stage: ingestion, hosting duration, review, and the final export.

Premier Legal Technologies built its approach to AI for eDiscovery around exactly this idea. AI-assisted review is part of the workflow from day one, not a surprise line item that shows up mid-matter.

Run Every Matter Like a Project, Not a Fire Drill

Even with good tech in place, costs drift when nobody owns the scope. Firms that keep eDiscovery costs under control treat every matter the same way: a documented scope agreed to before collection starts, clear custodian and date boundaries, defined recall targets for TAR, and budget checkpoints along the way instead of one estimate handed out at the start and never revisited.

This matters most in matters that start small and grow. A narrow discovery request can expand fast once new custodians or claims get added, and that kind of scope creep is exactly what turns manageable eDiscovery costs into a budget problem nobody saw coming. Without a process for reassessing scope and budget at each expansion point, costs pile up quietly until the invoice lands, and nobody can quite explain it.

A Real Example: Eight Terabytes, Half the Budget

This is where all of it comes together, or falls apart, depending on how the matter gets handled. Picture a mid-size firm staring down a commercial litigation matter with an estimated eight terabytes of potentially relevant data spread across email, shared drives, and a cloud collaboration platform, against a client budget sized for a fraction of that.

Handled the wrong way, all eight terabytes get processed and hosted in full, reviewed linearly by a mix of associates and contract attorneys, and the matter blows past budget well before review wraps, leaving the firm to explain overages to a client who was quoted something much smaller.

Handled the right way, it starts with a structured early case assessment. Deduplication and DeNIST filtering alone strip out 30 to 40% of raw volume before anything else happens. Date range and custodian scoping narrow things further based on what the case actually claims. A CAL workflow then prioritizes what's left, so reviewers see the documents that matter first instead of working through eight terabytes in whatever order it happened to load. What looked like an eight-terabyte problem becomes a review population a fraction of that size, with a documented reason for every cut along the way.

This isn't a hypothetical. In one recent engagement, Premier Legal Technologies took on a 600,000-document, three-terabyte review for an Am Law 100 firm under a strict four-week deadline. A 110-person review team ran the initial pass while Reveal's predictive AI worked in parallel, flagging roughly 20,000 documents the human team had tagged non-responsive but that scored 98% or higher as likely responsive. A targeted second-tier review of that flagged set surfaced nearly 2,800 additional responsive documents, a 13–15% boost in responsiveness, while shrinking the second-pass review team needed to get there. The review finished on deadline, and the firm walked away with a defensible record of exactly what the AI caught that a purely linear review would have missed. See the full case study.

That's the real difference between scrambling to manage eDiscovery costs after the fact and running a genuinely managed services eDiscovery engagement from day one. The second version isn't cheaper because less work got done. It's cheaper because the work that mattered got done first.

Get Ahead of It Before the Data Does

None of this works especially well in isolation. Early culling sets up a smarter TAR workflow. The right platform makes both easier to run and easier to budget. And none of it replaces a team that’s actually handled matters at this scale before.

If your firm has a matter where the data volume and budget aren’t aligned, or you’re not sure your current eDiscovery solution is controlling costs as it should, we can help you scope a strategy before the volume gets ahead of the budget. Check out our full eDiscovery services, or contact Premier Legal Technologies to talk through your matter.