Confidential AI product engineering
AI-Powered Sales and Operations Platform
I built substantial parts of a private AI-assisted sales and operations platform spanning CRM workflows, quotations, tasks, messaging, payments, referrals, dashboards, localization, and production AI/chat integrations.
- Role
- Full-Stack Product Engineer through HestiaForge
- Period
- 2025–2026
Confidential product system
AI assistance inside operational workflows
Client and CRM workflows
Quotations and documents
AI and streaming chat
Payments and billing
Context
Private client product
Role
Full-Stack Product Engineer through HestiaForge
Product type
Confidential AI product engineering
Core capability
React
Product context
Keeping a fast-moving operational product coherent
The product brings together client records, sales workflows, calculation and document processes, communications, billing, learning content, and operational visibility. The challenge was to connect conventional workflows with useful AI assistance without turning the product into disconnected demos.
Attribution anchor
What I was responsible for
I worked across the existing team product and its generated foundations, taking ownership of substantial feature areas and production fixes. I do not present the platform as a solo build, and its identity and private workflow details remain confidential.
Selected scope
Selected contributions
- 01
Implemented quotation and calculator workflows, client lookup and deduplication, tasks, alerts, referrals, and presentation templates.
- 02
Integrated specialist product and document workflows, including proposal and policy extraction, while keeping the public description intentionally generic.
- 03
Built messaging flows, streaming chat, conversation history and memory, and application integration with AI and agent tooling.
- 04
Delivered subscription, credit, public checkout, payment, and advisory-billing workflows.
- 05
Improved dashboards, localization, training and analytics surfaces, authentication, and production reliability.
Evidence, not reconstruction
System view
A simplified view of verified responsibilities and system relationships. It does not reproduce a private or historical interface.
Confidential product system
AI assistance inside operational workflows
A generic, evidence-led view that intentionally omits the private product interface and domain specifics.
Client and CRM workflows
Records, lookup, deduplication, tasks, alerts, and referrals.
Input
Quotations and documents
Calculations, presentations, proposal and document extraction.
Process
AI and streaming chat
Conversation history, memory, agent integration, and reviewable assistance.
Process
Payments and billing
Subscriptions, credits, checkout, and advisory billing workflows.
System
Operations and analytics
Dashboards, localization, training, analytics, and reliability.
System
Production product flow
Connected capabilities usable inside day-to-day sales and operations.
Output
Verified relationships
- Client and CRM workflowsQuotations and documents
- Quotations and documentsAI and streaming chat
- Client and CRM workflowsPayments and billing
- AI and streaming chatOperations and analytics
- Payments and billingProduction product flow
- Operations and analyticsProduction product flow
Engineering judgment
Selected technical decisions
Decision 01
Used Supabase/PostgreSQL and Edge Functions as a practical backend for authentication, data, and workflow services.
Decision 02
Connected AI SDK and agent-based chat capabilities to existing operational workflows rather than presenting AI as a separate demo.
Decision 03
Combined typed forms and validation, React Query state, analytics, and incremental production hardening to support rapid product iteration.
Technology context
- React
- Vite
- TypeScript
- Supabase
- PostgreSQL
- Edge Functions
- React Query
- AI SDK
- Mastra
- Payment workflows
- PostHog
- D3 / Recharts
- React Hook Form
- Zod
- i18n
Delivered capability
“Connected product areas moved from iteration into production-ready operation across frontend, data, workflows, payments, integrations, localization, analytics, and reliability.”
AI product features · Operational workflows · Full-stack delivery