How much does it cost to build an app like Everlaw?
Estimated US development cost, the features and surfaces involved, the team and timeline it takes, the infrastructure it needs at scale, and what it costs to run once it is live.
A litigation platform for electronic discovery: ingesting large volumes of documents and communications, processing and de-duplicating them, enabling review and coding by legal teams, and supporting analysis, storytelling and production of relevant material to opposing parties.
What this build involves
Ediscovery & litigation- Features listed
- 38
- Sides served
- 4
- Industry
- Legal & professional services
- Sensitivity
- 4/5
The calculator returns
It is not one app — it is 4
The most common reason a budget for something like this comes in low is counting one application when the product needs several, plus the shared platform underneath that nobody sees.
Applications people use — 4
Document review
Web
Reviewing attorneys and contract reviewers
High-speed review, coding, search, redaction and threading. Latency here is money.
Case strategy tools
Web
Litigation teams
Chronologies, depositions, storybuilding, exhibits and analysis across the record.
Ingestion & processing pipeline
Web
Internal and litigation support
Format extraction, de-duplication, OCR, metadata normalisation and index building at scale.
Matter administration
Web
Litigation support and IT
Users across firms and clients, permissions, production sets, audit and data disposition.
Shared platform underneath — 9
Backend & API
The shared data model, business rules and the API every side reads and writes through. Built once, and the single largest line in almost every estimate.
Identity & permissions
Sign-in, sessions, second factors and a role model enforced on the server. Multi-sided products need one identity system that understands several kinds of user.
Notification system
Templating, preferences, delivery across push, email and SMS, retries, and the suppression rules that stop a product becoming spam.
Real-time transport
Persistent connections, presence, fan-out and reconnection. A separate scaling problem from the request/response API, with its own capacity model.
Media pipeline
Upload, transcode, storage, delivery and the CDN in front of it. Egress is usually the largest single running cost in a media product.
AI services & governance
Model access, retrieval over your own content, evaluation and guardrails. The governance half is the part that gets cut and then rebuilt after an incident.
Admin & operations console
Where your own staff fix what customers cannot: account issues, refunds, overrides, escalations. Consistently underbudgeted, and consistently the reason support costs balloon.
Analytics & reporting
Event instrumentation, a warehouse and the dashboards the business actually runs on. Retrofitting instrumentation costs several times what building it in does.
Infrastructure & delivery
Environments, pipelines, secrets, monitoring, alerting and on-call. The work that makes everything above deployable more than once a month.
What has to be built
Split by the phase each capability realistically lands in. The MVP column is priced as its own configuration above, so the split is a real costing decision rather than a diagram.
MVP features
13The smallest set that is still this product.
- Email & password sign-in
- Multi-factor authentication
- Enterprise SSO (SAML / OIDC)
- User profiles
- Organisations & team accounts
- Roles & permissions
- Documents & file handling
- Dedicated search engine
- Search, filters & sorting
- Audit logging
- Dashboards & reporting
- Version history
- Admin console
Advanced features
14What a credible competitor is expected to have.
- Document extraction (OCR)
- Retrieval over your own content
- Image & document understanding
- Approval workflows
- Self-service report builder
- Image upload & processing
- Video streaming & playback
- Notification centre
- In-app messaging
- Transactional email
- Accessibility (WCAG 2.2 AA)
- Multi-language support
- Time capture
- Retention & deletion policy
Enterprise features
11Scale, governance and the work nobody demos.
- Data warehouse pipeline
- Scheduled exports & feeds
- Public API & webhooks
- Anomaly detection
- Text generation & summarisation
- AI evaluation & guardrails
- Feature flags & remote config
- Support tooling
- White-labelling & theming
- Consent & authorisation records
- Compliant secure messaging
The same features, by who uses them
Customer experience
What the people you are building for actually touch.
- Email & password sign-in
- Multi-factor authentication
- Enterprise SSO (SAML / OIDC)
- User profiles
- Organisations & team accounts
- Roles & permissions
- Documents & file handling
- Audit logging
- Version history
- Document extraction (OCR)
- Image upload & processing
- Video streaming & playback
- Time capture
- Retention & deletion policy
- Consent & authorisation records
Communication
How the product reaches people and how they reach each other.
- Notification centre
- In-app messaging
- Transactional email
- Compliant secure messaging
Operations & staff
The consoles your own team lives in. Rarely demoed, always needed.
- Admin console
- Approval workflows
- Support tooling
Data & intelligence
Reporting, analysis and anything model-driven.
- Dedicated search engine
- Search, filters & sorting
- Dashboards & reporting
- Retrieval over your own content
- Image & document understanding
- Self-service report builder
- Data warehouse pipeline
- Scheduled exports & feeds
- Anomaly detection
- Text generation & summarisation
- AI evaluation & guardrails
Platform
The cross-cutting obligations — access, languages, configuration.
- Accessibility (WCAG 2.2 AA)
- Multi-language support
- Public API & webhooks
- Feature flags & remote config
- White-labelling & theming
Technology a build like this would use
Derived from the platforms and capabilities above.
These are typical choices for building a product of this shape today. They are derived from the platforms and capabilities described above — not a claim about what Everlaw actually runs on. We do not publish other companies’ internal technology, and you should be sceptical of anyone who does.
Web
- TypeScript
- React with Next.js
- Tailwind CSS or a component library
Server rendering matters here if the pages need to be indexed; if the web surface is an authenticated console only, it does not.
Backend
- Node.js or Go for the real-time edge
- Python or Java for domain services
- gRPC or REST between services
A real-time product usually ends up with two server profiles: a connection-handling tier tuned for many idle sockets, and a conventional application tier behind it.
Data
- PostgreSQL (primary transactional store)
- Redis (cache, sessions, queues)
- Elasticsearch or Algolia (search)
- Snowflake or BigQuery (analytics warehouse)
- pgvector or a managed vector database
One relational database plus a cache covers more products than teams expect. Add a specialist store when a real query pattern demands it, not in anticipation.
Cloud & delivery
- AWS, Google Cloud or Azure
- Containers on a managed orchestrator
- Terraform or equivalent for infrastructure as code
- GitHub Actions or similar for CI/CD
The architecture tier this product needs is driven by traffic, not preference — see the scale section below.
Messaging & notifications
- APNs and FCM for push, usually via a delivery service
- Twilio for SMS and voice
- SES, SendGrid or Resend for email
Deliverability is an operational discipline: warm-up, domain authentication, bounce handling and suppression lists. It is not solved by picking a vendor.
Video
- Mux or Cloudflare Stream for VOD
- A CDN in front of everything
- Signed URLs for access control
Building video transport in-house is a multi-year specialism. Buy the transport; spend your engineering on the product around it.
AI
- A hosted model provider (Anthropic, OpenAI) or Bedrock
- Retrieval over your own content with a vector index
- Evaluation harness and output guardrails
Token cost scales with usage, so unit economics need modelling before launch. The evaluation and guardrail layer is what separates a demo from a product.
Observability
- Sentry for errors
- Datadog, Grafana or an equivalent for metrics and traces
- Structured logging with retention matched to your compliance regime
Instrumentation is cheapest when added during the build. Retrofitting it after the first production incident costs several times more.
How an app like Everlaw works
Discovery means processing enormous, messy document collections — email archives, chat exports, files in hundreds of formats — extracting text and metadata, de-duplicating, and making everything searchable within a deadline set by a court. Review teams then read documents at high speed, so interface latency directly determines cost. Predictive coding uses reviewer decisions to prioritise the remaining set. Production must apply redactions permanently and generate documents in court-specified formats.
In costing terms that shape matters more than the feature count. A records & documents in legal & professional services inherits obligations before anyone designs a screen — this sector rates 4 out of 5 for regulatory and procurement difficulty on this site, and that rating is what drives the security posture, the audit work and the integration surface any estimate has to carry.
MVP versus the full product
A first version of this is a materially smaller build than the mature product, and the calculator will show you by how much. It gets there by shipping fewer features, on fewer surfaces, at a launch-sized audience rather than the traffic the mature product carries.
What it does not cut is compliance. A regulated product is regulated from its first user, so the primary regime stays in the MVP even though almost everything else is deferred. Teams that defer it discover that retrofitting audit logging, access control and data retention costs several times what building them in would have.
Monetisation
How products of this shape make money
- Data volume and per-matter pricing
- Per-user subscriptions
- Enterprise and government agreements
- Professional services and hosting
Generic to the category, not a description of Everlaw’s commercial arrangements.
What these numbers are, and are not
This page carries no figures deliberately. What it sets out is the shape of the build — the sides, the tiers, the stack, the compliance — because that is what an estimate is derived from and what you can check. The calculator turns your own version of that shape into a planning estimate with a stated confidence band; use it to decide the order of magnitude, then spend two to four weeks on a technical specification and get a real quote against that document.
Nothing here is a statement about Everlaw as a company. We do not know and do not publish what any business spent building its product, what it earns, how many people it employs, or what technology it runs on. What we describe is the product shape any user can observe — the surfaces it presents, the roles it serves, the capabilities it evidently has — and what building that shape would cost in the United States today.
Building an app like Everlaw, answered
How much does it cost to build an app like Everlaw?
There is no one figure, because "an app like Everlaw" covers three very different builds: a first version with only the essential features, a complete and credible competitor, and a rebuild of everything the mature product does at the traffic it carries. Those are several-fold apart. What this page gives you is the shape of each — the sides, the feature tiers, the stack and the compliance — and the calculator turns whichever one you actually mean into a cost range, hours and a timeline.
Why is an app like Everlaw more expensive than a typical app?
Because it is not one app. It is 4 separate applications — document review, case strategy tools, ingestion & processing pipeline, matter administration — sharing one backend, each with its own design, release cycle and test matrix. Most quotes that come in low have counted one of them. Ingesting anything, correctly, fast: Email archives, chat exports, spreadsheets, images and hundreds of legacy formats must be extracted, de-duplicated and indexed against a court deadline. The processing pipeline is the largest engineering investment.
Could I build a cheaper version first?
Yes, and you should. A first version ships the essential feature tier rather than all three, on fewer surfaces, at a launch-sized audience — materially less than the full product, and the calculator will show you by how much. What it does not cut is compliance: legal & professional services obligations apply from the first user, so those stay in whatever else is deferred.
How long would it take to build?
It depends on the same three things the cost does — which tier of the product you mean, how many surfaces you ship, and how settled the scope is. The calculator returns a timeline alongside the cost, derived the same way: hours divided across a realistic team shape, never a target date worked backwards from.
What does it cost to run once it is live?
Cloud infrastructure, third-party services and annual maintenance, and the calculator reports all three separately from the build. They are kept out of the build figure deliberately: they are operating expenditure rather than capital, and adding the two together produces a number that means nothing. Maintenance in particular is not optional — an app that receives none stops working within about a year as OS releases and SDK deprecations accumulate.
Are these real figures for Everlaw?
This page carries no figures at all, and nobody outside the company has real ones. What it describes is the product SHAPE, observed from what any user can see — the sides, the feature tiers, the stack, the compliance. Nothing here describes what Everlaw actually spent, earns, employs or runs on. The calculator prices building something of that shape today, for the United States market, at our own blended delivery rate.
Can we use AI for drafting and document review?
Yes, and clients increasingly expect it, but the professional liability changes the engineering. Every AI output needs source attribution, a human review step and an audit record of who accepted what. Retrieval over the firm’s own documents rather than open-ended generation is the pattern that works. Budget $50,000–$120,000 for a properly grounded, evaluated implementation — most of that in retrieval quality and evaluation rather than the model call.
How accurate is this estimate?
It is a planning estimate, not a quote. The band shown is roughly plus or minus 15–20% for a well-defined scope, and wider while requirements are still moving. It is built from engineering hours per discipline, converted at our blended delivery rate, so the hours are directly comparable to a real proposal line by line — but a firm price needs a technical specification, which is the step after budgeting.
Similar apps, priced the same way
Products with a comparable shape. Each has its own breakdown.
Price your own build, not Everlaw's
Every control on one page, a live spec sheet beside it, and nothing behind a form.