RapidCanvas

RapidCanvas + Google Cloud

  • Google Cloud Partner
  • Direct today

A Google Cloud Partner. BigQuery in. Vertex out.

BigQuery is already your source of truth, and the governance around it took years to get right. Vertex already gives you the models. What is missing is the layer that turns a governed schema into decisions people act on. RapidCanvas sits there, reading BigQuery in place and calling Vertex for inference, so BigQuery stays the single source and every decision traces back to the column it came from rather than to a copy nobody owns.

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12

Google Cloud use cases documented

7

use cases already in production

10

Google Cloud and Workspace services in use

How it fits

  • Google Cloud Partner, listed in the Google Cloud Partner Directory
  • Vertex AI as a model backend: Gemini family, Claude on Vertex, partner models
  • Standard connectors to BigQuery, Cloud Storage, Pub/Sub, Dataflow
  • IAM-scoped service accounts for RapidCanvas to Google Cloud calls

Why Google Cloud customers choose this

  • BigQuery stays the source of truth; AI delivery uses it without rebuilding governance elsewhere
  • Vertex consumed through a production AI platform, not as a raw model call

Google Cloud holds the governed source of truth and the models. RapidCanvas turns them into decisions people act on. Together they get a BigQuery investment working beyond the dashboard.

ProcurementDirect todayGoogle Cloud Marketplace listing on roadmap
Reference Architecture

How RapidCanvas Builds on Google Cloud

The same shape recurs across every use case: scoped service-account credentials, data from Google Cloud, Gemini behind a validation layer, and RapidCanvas assembling the result for a business user.

The same three-lane shape recurs across all twelve use cases: Business, RapidCanvas, and Google Cloud.

Built to keep Gemini output checked before it ships.

Credentials stay scoped

IAM service accounts, scoped to the project, held in RapidCanvas Secrets rather than in code or config files.

Data stays in place

BigQuery, Cloud SQL, Cloud Storage and Drive are read where the customer already governs them, not copied elsewhere first.

Models sit behind validation

Gemini output is schema-checked, confidence-scored and, below threshold, routed to a person before anything is written.

Use Cases

12 Use Cases on Google Cloud

Customer names are withheld. Every story below is a real RapidCanvas deployment, verified against the delivered code.

Private wealth management, Latin America

Custody Statement Reconciliation Runs on Gemini

  • Gemini
  • Cloud SQL
  • Cloud Storage

A multi-family office reconciles custody and bank statements from dozens of institutions, each in its own layout, against its portfolio system. RapidCanvas extracts and matches positions with Gemini through its model gateway, using signed Cloud Storage URLs so documents never touch the model directly, then applies pricing rules before writing results to Cloud SQL and the office's own systems, with a person reviewing anything the rules and the model disagree on.

Live in production; a rate-limiter fix cleared a processing backlog incident.
Construction compliance, North America

Five Payroll Documents, Parsed and Joined in Cloud SQL

  • Gemini
  • Cloud SQL

A general contractor must prove that certified payroll, timesheets and paystubs agree for every worker on public-works projects, with correct apprentice pay ratios, across documents that arrive as PDFs in dozens of layouts. RapidCanvas parses all five document types with Gemini, joins them by worker identity with model-assisted name matching, computes expected pay, and writes flagged discrepancies to Cloud SQL for review in a compliance dashboard instead of manual document-by-document checking.

Live in production; a project run takes thirty minutes to two hours.
Electronics manufacturing, global

Grounded Gemini Signals Prioritize New Sales Accounts

  • Gemini
  • Google Maps Platform

A global electronics manufacturer's sellers needed prioritized new accounts across two fast-moving verticals, with evidence they could cite and results refreshed weekly, something generic web search could not deliver at the right freshness or specificity. RapidCanvas runs region-split Gemini queries with Google Search grounding and citation harvesting, filters stale signals, classifies company fit, and scores leads into a Data App sellers use to prioritize outreach.

One run qualified most companies it classified from an initial seed list.
Public infrastructure, Africa

Roadside Insurance Cards Read by Gemini When Codes Fail

  • Gemini

A road authority enrols cross-border trucking fleets from insurance cards, but the QR code that should identify each truck often fails in the field, leaving staff to transcribe faint identifiers from glared, stamped phone photos by hand. RapidCanvas built a Gemini vision pipeline with a bilingual, layout-aware prompt and a confidence-gated review step for the two fields that must be exactly right, returning cost per extraction so the authority can track spend.

Deployed in production; benchmarked at 100 percent on the internal sample.
Public infrastructure, Africa

Dashcam Video Meets GPU Inference on Google Cloud

  • Compute Engine
  • Cloud Storage

A road authority inspected corridor defects by driving segments manually, wanting GPS-tagged evidence and repair-budget estimates instead. RapidCanvas built a video pipeline that streams dashcam footage to a vision detector running on a Compute Engine GPU machine, stages large uploads through Cloud Storage, and lets reviewers confirm detections in a Data App. Labelled frames feed retraining, so a better model is promoted by changing an alias, not by redeploying anything.

Live since 2026; the authority reports fewer field visits.
Professional services, global

Chat Analytics Flow From BigQuery Into Cloud SQL

  • BigQuery
  • Cloud SQL
  • Datastream

Administrators of an internal knowledge assistant needed usage and quality analytics without querying the live chat database directly, after a first design saturated it under just a handful of concurrent reads. RapidCanvas now replicates the chat data into BigQuery with Datastream change-data capture, syncs it into a Cloud SQL analytics database every thirty minutes, and serves usage, quality and time-saved reporting to administrators from a materialised fact view.

Live since 2026; sync completes in about ten seconds every half hour.

6 More Use Cases in the Full Case Study

  • A Five Schema Lakehouse Built on Cloud SQLReal estate development, Latin America · In production
  • Wealth Documents Classified and Extracted by GeminiWealth management technology, North America · Pilot
  • Restaurant Invoices Move From Drive Into a LedgerHospitality and restaurants, global · In delivery
  • A Test Coverage Assistant Reads a Live SheetEnterprise software, global · In delivery
  • A Gemini Pipeline Scopes Bids for EstimatorsConstruction estimating, North America · Proof of concept
  • Structured Extraction and Managed Databases, RepeatedMultiple industries, global · Reference pattern
Download complete case study PDF

Google Cloud questions

Not yet. RapidCanvas is a Google Cloud Partner and listed in the Google Cloud Partner Directory, and today the commercial relationship is direct. A Marketplace listing is on the roadmap.
Yes, where Google-resident inference is preferred. The Gemini family, Claude on Vertex and partner models are all available as backends, consumed through the platform rather than as raw model calls, so evaluation and lineage come with them.
Through IAM-scoped service accounts, so it holds only the permissions your project has granted it. It reads governed BigQuery datasets along with Cloud Storage, Pub/Sub and Dataflow, and BigQuery stays the source of truth rather than being copied elsewhere.

Also runs on

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