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Seraf

אודות הפרויקט

Seraf AI is an AI assistant built specifically for manufacturing companies and their front-office teams — sales, customer support, and coordination — letting them get instant answers to work questions without changing existing systems or involving IT, deploying in just 7 days. One of our developers worked on this project, contributing full-stack across multiple features.

סקירת הפרויקט

The platform delivers a full-stack investment management experience for every type of early-stage investor: from individual angels tracking personal portfolios, to VC funds and family offices managing complex multi-fund structures — with automated reporting, KPI collection, document intelligence, and LP-facing portals built into a single product. Our contribution came from a single developer working across both frontend and backend areas of the platform.

Project Goal

מטרת הפרויקט

The goal of the project was to replace the patchwork of spreadsheets, email threads, and disconnected tools that early-stage investors rely on, and consolidate everything — deal flow, portfolio tracking, reporting, document analysis, and LP communication — into one reliable, professional-grade platform. A key focus was placed on saving time through automation, AI-assisted document handling, and direct data integrations.

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Solution

הפתרון

Our developer contributed across several areas of the platform: fixing form behavior and strengthening password-change validation; building out document chunk functionality end-to-end — chunk sharing, relation management, chunk-scoped chat, and state sync after deletions; adding bookmark functionality with quick-question suggestions; optimizing chatbot response performance; implementing a feedback feature with like/dislike controls and an outbound mailing flow; running data migrations and building a QuickBase/QuickBooks extraction script; and handling fixes across Overview Settings and naming consistency.

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אתגרים מרכזיים

  • Early-stage investors manage dozens of portfolio companies across fragmented tools — spreadsheets, email, and manual cap table tracking — with no single source of truth

  • Large volumes of unstructured documents (reports, agreements, updates) are hard to search, relate, and discuss without dedicated chunk-level tooling

  • Reporting to LPs, accountants, and lawyers is time-consuming and error-prone when built manually from raw data

  • Migrating and syncing data from external accounting/sandbox systems requires careful, repeatable extraction logic

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תכונות מרכזיות

  • Document Chunk Intelligence — Share, relate, and chat with individual document chunks: create, update, and delete relations between chunks, start a dedicated chat scoped to a specific chunk, and keep document lists and local state correctly synced after edits or deletions.

  • Bookmarks & Quick Questions — Save and revisit key points in documents or conversations, with quick-question shortcuts that speed up common lookups.

  • Feedback & Response Quality — A feedback system with like/dislike controls and an integrated mailing flow, paired with ongoing optimization of chatbot response performance.

  • Reliable Forms & Validation — Fixed form-reset behavior after user-creation submission and tightened password-change validation to prevent silent state or security issues.

ממשק סופי

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סקירת תכונות

Investment Portfolio Management

A full-stack investment management platform — track deal flow, manage portfolio companies, generate white-labeled LP reports, and give stakeholders secure portal access, all from a single unified system.

Features overview
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מחסנית טכנולוגית

Built on a Python backend with a React and TypeScript frontend, PostgreSQL for data storage, AWS infrastructure, Stripe for billing, and OpenAI powering the conversational AI layer.

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מדדים

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Days to deploy

Designed for on-premises deployment within 7 days, with no consultants or dedicated IT support required to get started.

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Developer, full-stack

A single developer from our team contributed full-stack — across RBAC, document/chunk handling, bookmarks, integrations, and data migrations.

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Systems integrated

Connected the assistant to ERP (SAP, NetSuite, Acumatica), CRM (Salesforce, HubSpot), SharePoint/OneDrive, and additionally Intuit/QuickBooks, Google Drive, and Notion.

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On-premises deployment

Built to run on-premises so manufacturing data and customer information are never shared with third parties.

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