Databricks Software / SaaS United States

Anyclip

Enterprise Knowledge Search · Marketing Personalization

AnyClip is a visual intelligence company whose AI-powered platform turns traditional video into interactive content that is fully searchable, measurable, personalized and monetized for consumer and corporate audiences. AnyClip’s client roster includes Fortune 500 companies with huge video libraries, which AnyClip tools analyze frame by frame, recognizing people, brands and topics among other data points — all of whic

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1 million+ Videos analyzed in the database

25% Overall cost savings

98% Improvement in query performance

But when I have a huge data model, I can scale and it’ll be much cheaper — overall about 25% cheaper and close to 50% faster — and very accurate.

Reported impact

Business outcome

Solution

Anyclip built its Databricks implementation around Databricks SQL, Apache Spark Declarative Pipelines, Delta Lake, Apache Spark. AnyClip is a visual intelligence company whose AI-powered platform turns traditional video into interactive content that is fully searchable, measurable, personalized and monetized for consumer and corporate audiences. AnyClip’s client roster includes Fortune 500 companies with huge video libraries, which AnyClip tools analyze frame by frame, recognizing people, brands and topics among other data points — all of whic. Databricks SQL serves governed analytics, dashboards, and ad hoc queries for business users and operational teams. Apache Spark Declarative Pipelines builds transformation pipelines over shared data with Spark-based processing. Delta Lake stores curated lakehouse tables with ACID guarantees for downstream analytics and machine learning. Apache Spark processes large-scale transformations and analytics over unified datasets.

Data flow

Source data and events are ingested through managed connectors, files, or streaming feeds into databricks, curated in Delta Lake tables, processed with Databricks compute and orchestration services, and served through analytics, semantic search, or model endpoints for downstream users and applications. It connects with BigQuery, Redshift.

Solution architecture

6 components · 4 layers

Ingest
- BigQuery Acts as a remote analytics source queried alongside Databricks data.
Compute
- Apache Spark Declarative Pipelines Builds transformation pipelines over shared data with Spark-based processing.
- Apache Spark Processes large-scale transformations and analytics over unified datasets.
Storage
- Delta Lake Stores curated lakehouse tables with ACID guarantees for downstream analytics and machine learning.
- Redshift Represents a legacy warehouse replaced or simplified by the new platform.
Serving
- Databricks SQL Serves governed analytics, dashboards, and ad hoc queries for business users and operational teams.

Architecture clues

Apache Spark
Apache Spark Declarative Pipelines
Databricks SQL
Delta Lake
Overall cost savings
Time-consuming data queries lead to frustration

Evidence from the source

1 million+ Videos analyzed in the database

98% Improvement in query performance

Accomplishing this wasn’t always easy. With the previous data stack using Redshift, queries yielded widespread frustration rather than insights.

Another example is how the rush for reporting on Monday mornings, when everyone comes back from the weekend and wants the latest data, has changed. “All the reports were scheduled for the exact same time, and previously, everything got stuc

Using materialized views in Databricks SQL had immediate and profound impacts for AnyClip. “We’ve seen query performances improve by 98% with some of our tables that have several terabytes of data,” affirmed Doron.

With more videos arriving daily — total video inventory is now in the millions — costs and inefficiency were growing. “We very quickly got to a point where we had two options: Either scale enormously in terms of machines in Redshift, which

Transparency Evidence & methodology 96/100 reference value · 94% confidence · 3 sources

Review how this reference was scored and trace each normalized claim back to its documented source.

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value96/100

Problem clarity20/20
Measures whether the customer's operational problem is specific enough to compare.
Implementation depth25/25
Rewards named components, data flow, integrations, and architecture detail.
Outcome specificity16/20
Measures whether the reported benefit is concrete rather than a generic claim.
Quantified impact25/25
3 metrics describe measurable impact.
Deployment scale10/10
Rewards evidence of a live or scaled deployment and meaningful integration scope.

Evidence confidence94%

Source authority20/25
The main evidence is an official vendor-published customer story.
Claim traceability25/25
12 of 12 key fields link to a named source.
Direct evidence20/20
6 direct source quotes retained.
Date provenance10/10
The publication date comes from the source page or publisher.
Source transparency9/10
3 source references document publisher, URL, authority, retrieval, and supported fields.
Implementation specificity10/10
Rewards source-backed components, data flow, quantified impact, and a specific outcome.

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

Databricks
Anyclip customer story

First-party
https://www.databricks.com/customers/anyclip

Source type
Vendor-published customer story

Published
May 24, 2024
Supports
- Customer
- Business problem
- Solution
- Products
- Solution components
- Data flow
- Integrations
- technical area
- use case category
- Business outcome
- outcome category
- Metrics
- Architecture
- evidence quotes
- Publication date
AnyClip
Contact | AnyClip

First-party
https://anyclip.com/contact/
AnyClip's contact page lists "New York (HQ)" at "122 Grand St, New York, NY 10013."

Source type
Official company website
Supports
- Region
Revelio Labs
Anyclip Number of Employees 2026 | Employee Count & Headcount Data

Independent secondary
https://www.reveliolabs.com/companies/anyclip/employees
The workforce profile reports 217 employees as of March 2026.

Source type
Structured company profile
Supports
- Company size

Date evidence

Published on source page May 24, 2024 · Databricks · First-party
Open date source

Not separately sourced Industry. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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