Google Cloud Financial Services United States

Raylu

Sales Automation

Founded in 2022, Raylu is building the AI origination engine for private markets, replacing static tools and manual research with an always-on system designed for the speed of modern investing.

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Doubled company annual recurring revenue over three consecutive quarters

Reduced API costs by consolidating multiple LLM calls into fewer requests

Scaled infrastructure as Raylu grew from three to 30 employees

Reported impact

Business outcome

Doubled company annual recurring revenue over three consecutive quarters; Scaled infrastructure as Raylu grew from three to 30 employees; Supported growing demand from private-market investment firms; Reduced API costs by consolidating multiple LLM calls into fewer requests.

Solution

Raylu built its AI origination engine on Google Cloud and Gemini, closing the gap between investor conviction and deployed capital. Founded in 2022, Raylu is building the AI origination engine for private markets, replacing static tools and manual research with an always-on system designed for the speed of modern investing. The company identified a structural problem in private markets: investment teams were relying on static databases, spreadsheets, and manual research processes to compete in markets moving faster than their infrastructure. Raylu saw an opportunity to rebuild the origination process around AI. Its AI origination engine combines public information with proprietary firm data to map markets, prioritize relevant companies, identify emerging signals, and support earlier founder engagement.

Solution architecture

5 components · 4 layers

Storage
- Cloud SQL Stores transactional state and application data for the operational workflow at low latency.
Orchestration
- Gemini platform Provides the reasoning or generation layer used for classification, orchestration, content generation, or analysis.
Governance
- Security Command Center Provides continuous asset discovery and vulnerability scanning across the environment.
Uncategorized
- Redis Supports a core part of the deployed AI and data workflow described in the customer story.
- Google Cloud Secret Manager Supports a core part of the deployed AI and data workflow described in the customer story.

Architecture clues

Gemini platform makes it straightforward to evaluate and switch between models as our requirements evolve. That flexibility has helped us consolidate model calls, improve our systems, and reduce API costs as we scale.
Google Cloud worked with Raylu to evaluate the architecture, anticipated usage, and economics of operating the platform at greater scale. Transitioning to a new platform required Samuel and Nathan to align Google Cloud’s capabilities and se
The dynamic nature of Gemini platform also makes it easy for Raylu to swap models during testing and development. Raylu consolidated multiple data-processing requests into fewer model calls, reducing API costs and simplifying its workflows.
To power its AI origination engine at scale, Raylu simultaneously performs tens of thousands of web queries, data-processing tasks, database actions, and LLM calls. To handle the immense throughput, Raylu integrated Gemini platform. The pla
“Gemini platform makes it straightforward to evaluate and switch between models as our requirements evolve,” says Ilkka. “That flexibility has helped us consolidate model calls, improve our systems, and reduce API costs as we scale.”
“We simultaneously run tens of thousands of research and data-processing workflows across the origination process. Gemini platform gives us the infrastructure and throughput needed to support growing customer demand.”

Evidence from the source

Doubled company annual recurring revenue over three consecutive quarters

Founded in 2022, Raylu is building the AI origination engine for private markets, replacing static tools and manual research with an always-on system designed for the speed of modern investing. The company identified a structural problem in

Raylu initially tested the experience through a simple form before developing the conversational interface customers use today. The team later developed a conversational interface that allows investors to express their strategies and resear

Reduced API costs by consolidating multiple LLM calls into fewer requests

Scaled infrastructure as Raylu grew from three to 30 employees

Supported growing demand from private-market investment firms

Transparency Evidence & methodology 80/100 reference value · 77% confidence · 1 source

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 value80/100

Problem clarity20/20
Measures whether the customer's operational problem is specific enough to compare.
Implementation depth15/25
Rewards named components, data flow, integrations, and architecture detail.
Outcome specificity20/20
Measures whether the reported benefit is concrete rather than a generic claim.
Quantified impact15/25
1 metric describe measurable impact.
Deployment scale10/10
Rewards evidence of a live or scaled deployment and meaningful integration scope.

Evidence confidence77%

Source authority20/25
The main evidence is an official vendor-published customer story.
Claim traceability21/25
10 of 12 key fields link to a named source.
Direct evidence20/20
6 direct source quotes retained.
Date provenance0/10
The publication date has no documented provenance.
Source transparency8/10
1 source reference document publisher, URL, authority, retrieval, and supported fields.
Implementation specificity8/10
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.

Google Cloud
Raylu customer story

First-party
https://cloud.google.com/customers/raylu

Source type
Vendor-published customer story
Supports
- Customer
- Business problem
- Solution
- Products
- Solution components
- Data flow
- Integrations
- technical area
- use case category
- Business outcome
- outcome category
- Metrics
- Architecture
- evidence quotes

Date evidence

Sitemap last modified Oct 9, 2026 · Google Cloud · Publisher metadata Publisher-reported modification timestamp; not a publication date.
Open date source
Unverified extracted date Oct 9, 2026 · Google Cloud · Unknown Legacy extracted date without source-page confirmation.
Open date source

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

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