How Ideas2IT Built the AI-Driven Emissions Platform That Took a Climate-Tech Startup From Concept to Enterprise Clients Live
The startup needed an enterprise-grade emissions platform fast, with strict data isolation and custom regulatory reporting. Ideas2IT built a multi-tenant SaaS platform with ML-driven emissions computation and automated report generation.
Client
Sustainable SaaS Startup
Industry
Technology
Service
App Development
Geography
USA
Engagement
Complete
01 Challenge
Enterprises had no accurate way to calculate emissions across operations and supply chains, or a path to compliant sustainability reporting. The startup needed a production-ready, multi-tenant platform ingesting 25+ data entities, with strict tenant isolation and zero lead time to build it.
02 Solution
Ideas2IT built the platform on JHipster and microservices for rapid, reusable scaffolding, with a multi-tenant multi-database architecture isolating each client's data by design. An ML model computed Scope 1, 2, and 3 emissions, dynamic logic linked 25+ data entities, and a dedicated Puppeteer service generated custom regulatory PDF reports.
03 Outcome
Enterprises got accurate, granular emissions computation and compliant Scope 1, 2, and 3 reporting at company and product level. New clients onboarded within weeks of delivery, and the client's team took over the codebase within one sprint.
Phase 01
Building a reusable, isolated foundation for every future tenant
Multi-Tenant Foundation on JHipster and Microservices
Ideas2IT decided the isolation model before writing a feature: a multi-tenant, multi-database architecture with role-based access control at the tenant level, since the platform held confidential emissions data for competing enterprises. JHipster gave the team reusable scaffolding to hit an aggressive go-to-market timeline.
On that base, the team built a User Management module for authentication and company onboarding, a Customer Data Upload module supporting single and Excel-based ingestion with automated ML triggers, and a CI/CD pipeline on GitHub Actions with Liquibase-managed migrations, wrapped in CloudFront-templated automation so tenant environments spun up without re-engineering isolation each time.
This phase produced
- Multi-tenant multi-database architecture
- Role-based access control framework
- User Management module
- Customer Data Upload module (single + Excel ingestion)
- GitHub Actions CI/CD with Liquibase migrations
- CloudFront-templated environment provisioning
Phase 02
Turning uploaded operational data into Scope 1, 2, and 3 emissions
Linking 25+ Data Entities Without Manual Mapping: From Upload to Emissions Output
Uploading more than 25 interdependent data entities meant a customer could upload a child record without its parent ever existing in the system. Ideas2IT built backend logic that dynamically inferred and maintained parent-child hierarchies on upload, paired with a validation framework that caught integrity gaps before they reached computation.
On top of that, the team integrated an external ML model as the emissions calculation engine for Scope 1, 2, and 3, wired a notification module for member invites and data processing, and built company-level and product-level dashboards so operators could see computation results without touching the underlying data model.
Deliverables:
- Dynamic parent-child relationship engine
- Upload validation framework
- ML-based Scope 1/2/3 emissions engine
- Notification module (invites + data processing)
- Company-level analytics dashboard
- Product-level analytics dashboard
Phase 03
Making sustainability reports fit any client's format on demand
Custom Regulatory PDFs at Scale: Company and Product-Level Reporting on Demand
Generating regulatory-grade PDFs across multiple industry-standard formats and per-client custom templates was too heavy to run inside the core application, so Ideas2IT split it into a dedicated Puppeteer-based report service.
The team built pre-defined templates for industry-standard sustainability reports alongside a customization layer for client-specific formats, exposed through a Report Service module handling generation and export at both company and product level. Kibana and Grafana gave the team near-real-time observability into report generation and platform health, with IAM, encrypted S3 and RDS, and Parameter Store securing tenant data across the stack
Deliverables:
- Puppeteer-based PDF report service
- Industry-standard report template library
- Client-specific report customization layer
- Report Service module (generate + export)
- Kibana/Grafana observability stack
- IAM, S3, RDS, and Parameter Store security layer
"We're nearing the end of our first sprint independent of the Ideas2IT team, and we feel comfortable owning the code. Thank you for supporting us."
The Outcome
The isolation-first architecture meant new enterprise clients could onboard without re-engineering data boundaries, and decoupling the ML and reporting layers meant compliance requirements could evolve without touching the core platform. That structural separation, not a feature list, is what let the client's own team pick up the codebase and run it independently within a single sprint.