Real Systems. Real Impact. Intelligent Infrastructure in Action.

Proof That Intelligent Infrastructure Works.

Every system we build tells a story — of time reclaimed, decisions accelerated, and automation that begins to think for itself through use.

Trusted by SaaS, consulting, finance, legal, and AI-first companies.

Below is a selection of recent intelligent infrastructure builds and the measurable impact they delivered.

Case Study 1

10x Faster Onboarding for a SaaS Platform

Client:

Fast-growing SaaS platform (anonymous by NDA)

Problem:

Reduced onboarding time from 5–7 days → 3 days. Built with modular workflows, unified data pipelines, and reasoning layers on top of Supabase + Redis cache.

Solution:

Operisys designed a Unified AI Onboarding Infrastructure:

  • Connected CRM, payment, and analytics tools via n8n + Supabase
  • Introduced an AI "Onboarding Assistant" trained on documentation
  • Automated status tracking + client comms via Telegram/Email bridge

Architecture Modules Used:

  • Workflow Engine
  • Multi-Agent Orchestration
  • Knowledge Layer (RAG)
  • Automation Pipelines
  • Decision/Reasoning Layer

Results:

+70% customer happiness

+92 NPS

5 dashboards merged into 1 system-brain

"It feels like we hired five extra people — but it's just our system finally doing what it should."

— SaaS Platform (under NDA)

Results:

+42% faster proposal delivery

8 minutes per draft

Central knowledge layer built

"Our AI now writes the first draft of every proposal — we just sign off and send. It's like having an assistant who never sleeps."

— Consulting Firm, UK

Case Study 2

Proposal Automation for a Consulting Firm

Client:

Boutique management consultancy (UK)

Problem:

AI-driven proposal generation, internal knowledge indexing, logic routing, and decision chains built to eliminate 6–10 hours of repetitive work weekly.

Solution:

We implemented a Proposal Automation & AI Knowledge Engine:

  • Supabase + OpenAI pipeline for dynamic proposal drafts
  • Integrated DocuSign & Stripe for instant contracting and payments
  • Automated "Proposal Follow-Up AI" with contextual replies

Architecture Modules Used:

  • Workflow Engine
  • Multi-Agent Orchestration
  • Knowledge Layer (RAG)
  • Automation Pipelines
  • Decision/Reasoning Layer
Case Study 3

Legal Intelligence Infrastructure for a Law Firm

Client:

Mid-size immigration & compliance law firm

Problem:

Systems built for immigration, compliance search, reasoning retrieval, and weekly policy summarization. Designed with GDPR-ready audit logs and training memory loops.

Solution:

Built an Internal Legal Knowledge Infrastructure:

  • Secure Supabase + OpenAI hybrid (with RLS for compliance)
  • Natural-language "Case Finder" for document retrieval
  • Weekly automated compliance summaries

Architecture Modules Used:

  • Workflow Engine
  • Multi-Agent Orchestration
  • Knowledge Layer (RAG)
  • Automation Pipelines
  • Decision/Reasoning Layer

Results:

20+ hours saved weekly

300+ templates indexed

GDPR + firm-isolated architecture maintained

"We went from chaos to clarity. The system doesn't just store data — it understands it."

— Immigration & Compliance Law Firm

Systems That Learn Instead of Just Deliver.

Case studies may show results. But what matters is the pattern: de-fragment, architect, orchestrate, and scale with ownership.

Your Company Could Be Our Next Case Study.

Start with a free AI Audit — we'll map your automations, expose bottlenecks, and design your Intelligent Infrastructure Blueprint.

"Automation is temporary. Infrastructure is permanent."

— Ashkan Gholizadeh

Operisys — Case-Driven Infrastructure for Founders Who Ship.