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Google Cloud Financial Services India

Allvest Securities Private Limited

Customer Service Automation · Sales Automation

The evolution of Allvest Securities Private Limited is rooted in a fundamental mission: bridging the gap between sophisticated capital markets and the millions of Indian investors seeking a transparent, ethical entry point.

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Achieved 99.9% uptime during peak trading hours on Google Cloud
Improved system latency by 30% for real-time Spanner workflows
This agentic UI allows researchers to analyze petabytes of historical market data through simple chat prompts, reducing server load and drastically cutting operational costs.

Reported impact

Business outcome

With a stable foundation in place, Allvest turned to Google Cloud to solve the "complexity barrier" of investing. Using , Allvest manages its transactional ledger with perfect concurrency.

  • Customer Experience
  • Productivity Improvement
  • Scalability

Solution

As the platform's vision grew, the limitations of its legacy infrastructure became the primary obstacle. These systems struggled to manage the high-concurrency demands required to maintain user trust during market volatility. To realize its goal of becoming an AI-first leader, Allvest migrated to a distributed, cloud-native architecture. Leveraging and an infrastructure-as-code model, the team executed a transition that replaced manual bottlenecks with automated agility. This technical foundation allowed Allvest to scale to over 100,000 users seamlessly, maintaining a critical 99.9% uptime that ensures the platform remains a reliable ‘source of truth' for the next generation of investors. With a stable foundation in place, Allvest turned to Google Cloud to solve the "complexity barrier" of investing. Using , Allvest manages its transactional ledger with perfect concurrency. To empower their research team, it implemented a "Talk to Data" feature using BigQuery .

Solution architecture

6 components · 3 layers
  1. Compute
    • Gemini API Provides the reasoning or generation layer used for classification, orchestration, content generation, or analysis.
  2. Storage
    • BigQuery Serves as the governed analytics and storage layer for high-volume operational data, features, and reporting.
  3. Orchestration
    • Gemini Enterprise Agent Platform Coordinates multi-agent workflows, tool calling, and governed automation across the application.
    • Gemini Enterprise Provides the reasoning or generation layer used for classification, orchestration, content generation, or analysis.
    • Agent Development Kit (ADK) Coordinates multi-agent workflows, tool calling, and governed automation across the application.
    • Agent Platform Coordinates multi-agent workflows, tool calling, and governed automation across the application.

Architecture clues

  • As the platform's vision grew, the limitations of its legacy infrastructure became the primary obstacle.
  • With a stable foundation in place, Allvest turned to Google Cloud to solve the "complexity barrier" of investing.

Evidence from the source

As the platform's vision grew, the limitations of its legacy infrastructure became the primary obstacle. These systems struggled to manage the high-concurrency demands required to maintain user trust during market volati
For the investor, the breakthrough is "AI-curated baskets." Instead of overwhelming users with thousands of stocks, Gemini Enterprise Agent Platform (Vertex AI) analyzes risk profiles to suggest optimized portfolios.
Gemini Enterprise Agent Platform (Vertex AI) Cloud Storage
Reduced support call center overhead by 90% using Gemini Enterprise Agent Platform
The most visible transformation is in customer experience. Allvest utilized its partner's expertise in AI orchestration to deploy an AI-powered chatbot and voice bot using Gemini Enterprise Agent Platform (Gemini API) an
Transparency Evidence & methodology 86/100 reference value · 77% confidence · 1 source

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

01

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 value86/100
  • 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 specificity16/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact25/25
    2 metrics 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
    5 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.
02

Traceability

Sources & provenance

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

  1. Google Cloud

    Allvest Securities Private Limited customer story

    First-party
    https://cloud.google.com/customers/allvest
    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 Jun 16, 2026 · Google Cloud · Publisher metadata Publisher-reported modification timestamp; not a publication date.
    Open date source
  • Unverified extracted date Jun 16, 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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