Technical Deep-Dive · Warner Bros. Discovery

Building an enterprise context layer on your data lake

How DevRev connects Snowflake, SAP, ServiceNow, and Oracle into one intelligence surface for instant insight.

× WBD

29 June 2026
01:30 PM IST

Demo session · ~60 minutes

Solutions first, not a sales pitch

Architecture, live capability demo, and a focused discussion on your enterprise data challenges.

01

Company & architecture

Brief intro to DevRev and how the platform connects to enterprise data lakes.

~10 min

02

Live demo

How Computer queries across Snowflake, SAP, and document stores to surface insights in natural language.

~25 min

03

Your use cases

Content lifecycle analytics, vendor intelligence, and finance self-serve — mapped to the platform.

~15 min

04

Q&A & next steps

Technical questions, integration requirements, and a proposed POC path.

~10 min

Note

This session is solution-oriented with relevant enterprise examples — ask anything as we go.

The challenge today

Data is everywhere — insight is nowhere

Your data team navigates 10+ systems to answer one business question. That shouldn't take days.

Pain point

Fragmented data

Business intelligence spread across Snowflake, SAP, ServiceNow, Oracle ERP, and documents — no unified view.

Pain point

Manual insight generation

CFO needs content ROI numbers? That means navigating 4 dashboards, 3 applications, and a week of analyst time.

Pain point

Trapped knowledge

Vendor MSAs, SOWs, contracts, and RFPs hold critical intelligence but aren't searchable or analyzable at scale.

What if one intelligent layer could sit above all your data and answer any question in seconds?

The platform

Data in. Intelligence out. Decisions accelerated.

Computer unifies your systems into one permission-aware memory, then reasons and acts across all of it — governed, observable, auditable.

Ready to connect Planned

Same model · same question Memory does the work, so the LLM doesn't

Other AI · fetches all 3.2M

Computer · sends only signal 157K

Memory filters & joins in SQL before the LLM sees the data — 95% fewer tokens, 5.5× faster, and the gap widens as your data scales.

Your use cases

Three problems, one context layer

Each maps directly to DevRev Computer's capabilities — no custom development required.

01 Content intelligence

Content lifecycle & franchise ROI

Analyze the complete lifecycle of movies and content franchises — from production costs through theatrical, streaming, and web series revenue.

Example: "Compare Harry Potter vs Spider-Man franchise ROI across all distribution channels over the last 5 years."

📊 Multi-source aggregation

02 Vendor intelligence

Contract & vendor insight extraction

Extract actionable intelligence from MSAs, SOWs, contracts, and RFPs. Track historical engagement and spend with strategic vendors like Deloitte.

Example: "Summarize all Deloitte engagements in the past 3 years — scope, spend, and renewal terms."

📄 Document reasoning

03 Finance self-serve

CFO & finance instant insights

Enable finance leadership with faster access to business and financial insights — no more waiting for analyst cycles or navigating multiple dashboards.

Example: "What is our content production spend YoY, and which genres have the highest ROI?"

💰 Executive reporting

How it works

Ask a question. Get a cited answer.

Computer reasons across your entire data estate — not just one database at a time.

VP, Data Platform What was the total production cost vs. revenue for the Harry Potter franchise across all channels?

Computer Based on Snowflake (content_analytics) + SAP (project_financials):
Production cost: $1.2B across 8 titles · Revenue: $7.7B theatrical + $2.1B streaming
Blended ROI: 7.2× — sourced from 2 systems

VP, Data Platform How does that compare to Spider-Man?

Computer Spider-Man (Sony co-prod): ROI 5.8× — lower due to rev-sharing, but streaming engagement 34% higher per title. Want the full comparison report?

Live demo follows

Integration

Connects to your existing stack

No rip-and-replace. Computer layers on top with secure, read-only connectors.

Snowflake

Data lake queries, content analytics, engagement metrics

Native connector

SAP

Financials, procurement, project costs, vendor master

Native connector

ServiceNow

IT operations, workflow data, request management

Native connector

Oracle ERP

Financial planning, budgets, actuals, GL data

Native connector

Also supported

SharePoint, Google Drive, Confluence (for documents) · Custom APIs via universal connector · SSO & RBAC inherited from your IdP

Discovery

Let's understand your priorities

A few areas we'd love to explore together.

01

Data landscape

Which systems hold your most-queried data today? How do analysts currently access cross-system insights?

02

Use case priority

Of the three use cases (content ROI, vendor intel, finance self-serve) — which would deliver most value fastest?

03

Governance & security

Data residency requirements, PII handling, role-based access needs, and approval workflows for production data.

04

Success metrics

What does success look like in 90 days? Time-to-insight reduction? Analyst hours freed? Specific KPIs?

Proposed path forward

From today to live POC in 4 weeks

A lightweight pilot scoped to one high-value use case — proving value before scaling.

1

This week — align on scope

Pick 1 use case (e.g., content franchise analytics). Define 5-10 representative queries. Identify the data sources needed.

2

Week 2-3 — connect & configure

DevRev SE team connects Snowflake + one ERP source. Build the knowledge graph. Configure permissions and test queries end-to-end.

3

Week 4 — validate & expand

Your data team tests real queries. Measure time-to-insight vs. current process. Decision point: expand to additional use cases or full rollout plan.

Let's build together.

One context layer. Every data source. Instant enterprise insight.

DevRev Team Solutions Engineering

devrev.ai