Disco Financial Model

Three product lines:

1. DISCO Ediscovery - cloud-native SaaS for legal document collection, processing, search, review, and production. Sold direct to law firms and corporate legal teams.
2. DISCO Managed Review - AI-powered document review service that replaces attorney armies; charges per document but operates at software-level margins by using AI to reduce review population.
3. DISCO Case Builder - referenced in market map and flywheel; early / next product.

Key value props:

• 30–50% savings on doc review legal fees vs. traditional approach
• Cases resolved months earlier via AI-prioritized review
• Centralized legal data repository with permission controls
• AI scores documents −100 to +100 per tag; pushes relevant docs to top; reviewer sees ~80% relevant docs vs. ~10% in linear review; only need to review ~30% of population to find all relevant documents

Differentiators: cloud-native multi-tenant architecture (competitors must rewrite from on-premise); lawyer-focused UX + direct sales model; AI/analytics trained by lawyer users → growing moat as data accumulates. >$75M product investment stated.

• Ediscovery software market: $14B, described as "nondiscretionary, countercyclical."
• Managed Review / productized legal services: described as "3–5× bigger TAM" than ediscovery software, implying ~$42–70B.
• No SAM or SOM figures provided.
• No independent market growth rate cited.
• Use cases described as nondiscretionary: litigation, investigations, compliance, privacy, data breach, FOIA, GDPR DSARs.

Ediscovery (SaaS/usage):

• Sold direct to law firms and corporate legal departments
• Pricing basis not explicitly stated; likely per-GB ingested or per-user seat (common in ediscovery); not disclosed in deck
• Billed as ARR (recurring) - cohort ARR charts shown

Managed Review (productized services):

• Priced per document reviewed ($1/doc explicitly stated in opioids case study)
• DISCO's model: AI culls the review population dramatically → charges on smaller population → creates software-level gross margins
• Competitor comparison: $5.7M charge at $1/doc for 5.7M docs vs. DISCO charge of $484,160 at $1/doc for 484,160 docs
• >100% dollar attach rate for buying logos (Managed Review customers also buy Ediscovery)

Professional Services:

• Appears as a third revenue line in ARR chart (smallest segment, dark blue)

Growth motion: land and expand - customers added and ARR grows 2–3× over 2–3 years per cohort; multiple case studies show monotonic ARR growth over 2–5 year customer histories

• ARR: Annual run rate shown growing steeply from Jan 2018 to Jul 2020 across all three product lines; no absolute ARR dollar figure labeled on y-axis - axis scale not readable from chart.
• Logos: Customer count shown growing from Jan 2013 to Jan 2020; steep acceleration from ~2017 onward; no absolute logo count labeled.
• NPS: 17 (2017) → 30 (2018) → 52 (2019). >50% of customers gave a 10/10 in 2019 survey (310 respondents gave a "10").
• Managed Review growth: "Eight figure scale; 500% YoY" growth - implies ~$10–99M revenue run rate growing 5× year-over-year.
• Cohort growth: "Cohorts grow 2×–3× over 2–3 years" with "7+ years of cohort revenue growth."
• Dollar net retention: Described as "high dollar and logo net retention" - no specific % given.
• LTV:CAC: Described as "compelling" - no specific ratio disclosed.
• Sales rep productivity: "Strong" - no $/rep figure given.
• Opioids case study: DISCO billed $484,160 (484,160 docs × $1/doc) vs. competitor would have billed $5.7M (5.7M docs); review completed after reviewing only 33% of review population (159,880 / 484,160 docs).

• Gross margins: Managed Review described as operating at "high software gross margins" and "software-level margins" due to AI culling. - no % given.
• LTV:CAC: Described as "compelling." No ratio disclosed.
• Net dollar retention: Implied >100% given cohort 2–3× growth over 2–3 years; Managed Review has ">100% dollar attach rates for buying logos."

Competitive landscape:

• Incumbent competitors unnamed but described as: on-premise or single-tenant, non-lawyer UX, channel-sales model
• DISCO's three-axis differentiation (cloud-native, lawyer-UX, AI/analytics) described as "very difficult for a competitor to catch up on all three simultaneously" after >$75M product investment
• AI models trained by user behavior → data flywheel moat: more matters → better models → greater adoption
• Cross-Matter AI: learnings from past matters applied to new ones; enables out-of-box models, compliance programs, real-time litigation prevention
• Growth flywheel: Ediscovery usage → satisfaction → Managed Review → satisfaction → Case Builder → expansion

Named competitors: not explicitly named in deck.

Team:

• Kiwi Camara - Founder & CEO; 8 years at DISCO; prior: Camara & Sibley (law firm)
• Sean Nathaniel - COO; 1 year at DISCO; prior: Upland Software (EVP & CTO)
• Michael Lafair - CFO; 3 years; prior: Offers.com (CFO), All Web Leads (CFO & GC), Morgan Lewis
• Andrew Shimek - CRO; 3 years; prior: Epiq (President, Legal Services & Ediscovery, $500M business), LexisNexis
• Keith Zoellner - CTO; 5 years; prior: Spredfast (CTO), StoredIQ (CTO, sold to IBM)
• Kent Radford - General Counsel; 8 years; prior: Vinson & Elkins, Pillsbury, Hogan Lovells
• Neil Etheridge - CMO; 5 years; prior: Recommind (VP Product Marketing, sold to OpenText), Autonomy/Interwoven
• Melanie Antoon - VP Professional Services; 1 year; prior: Inventus (SVP US Ops), Huron Consulting, Catalyst (sold to OpenText)
• Aaron Trull - VP Human Resources; 2 years; prior: BazaarVoice, AMD, H-P, Dell

Archetype + why: Hybrid SaaS ARR + usage-based services model. DISCO has two economically distinct revenue streams that must be modeled separately: (1) Ediscovery - recurring SaaS ARR with classic land-and-expand cohort dynamics; (2) Managed Review - per-document transactional revenue that is event-driven (matter-by-matter) but can be projected as a % attach of ediscovery ARR given stated >100% dollar attach rates. Professional Services is a third, smaller line. The cohort growth story (2–3× over 2–3 years) is central to the bull case and needs explicit cohort waterfall treatment.

Forecast horizon & granularity:

• Monthly for Year 1 (cash visibility; Managed Review is lumpy)
• Quarterly for Years 2–5
• 5-year horizon total (growth stage, pre-IPO narrative)

Key drivers & assumptions:

*Ediscovery ARR:*

• Starting ARR (as of Aug 2020): - not labeled; must be estimated or sourced externally.
• New logo adds per month:
• Average new logo ACV at land:
• Net dollar retention (Ediscovery):
• Logo churn:

*Managed Review:*

• Revenue: described as "eight figure scale, 500% YoY."
• Starting run rate:
• Growth rate Year 1: 500% YoY → deceleration modeled as
• Attach to Ediscovery logos: >100% dollar attach; model as a % of Ediscovery ARR at each cohort milestone
• Gross margin (Managed Review):

*Ediscovery gross margin:* -

*Opex:*

• S&M:
• R&D:
• G&A:

Scenarios (Base / Bull / Bear - which variables flex):

• Base: ARR growth ~80% Y1→Y2, decelerating to ~40% by Y5; Managed Review 150% Y1→Y2; blended gross margin 65–70%
• Bull: Net dollar retention hits 140%+; Managed Review sustains >200% growth through Y3; Case Builder lands and contributes a third ARR stream by Y3
• Bear: Managed Review decelerates sharply (lumpy matters; economic slowdown compresses litigation spend); new logo adds slow; ARR growth ~40% Y1→Y2

Required sheets / outputs:

1. Assumptions - all drivers centralized, color-coded vs.
2. Ediscovery Cohort Waterfall - monthly/quarterly new logo ARR × expansion curve × churn
3. Managed Review Revenue Build - matter volume × avg. doc count × $1/doc pricing × AI culling factor → effective realized revenue and gross profit
4. Consolidated P&L - IS by segment and blended; EBITDA bridge
5. Cash Flow - operating CF; burn rate; runway (critical for sizing the raise)
6. KPI Dashboard - ARR, logo count, NRR, LTV:CAC, gross margin %, Managed Review attach rate
7. Scenarios tab - Base / Bull / Bear toggle