Products & Engineering Demonstrations

In-House Products & System Architectures

Haskra builds and maintains its own AI applications and workflow systems alongside client implementation work. Below, we clearly distinguish between our active product demonstrations, deployable workflow architectures, and longer-term research roadmap.

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Product Demonstration • Active Build

Academic Manuscript Review & Evaluation Engine

Haskra Scholar

A full-stack AI-assisted manuscript evaluation application designed for structured academic review. Users configure review objectives, scope, and discipline metadata, while the backend orchestrates section-by-section LLM prompt templates and streams real-time progress via Server-Sent Events (SSE).

Technical Scope & Capabilities:

Configurable multi-section review workflow (Introduction, Methodology, Literature, Results)

Sequential LLM prompt template execution with structured JSON scoring

Real-time section progress streaming via Server-Sent Events (SSE)

PostgreSQL / Prisma database architecture with JWT auth and credit tracking

Next.js + Express + Prisma + SSERequest Technical Walkthrough

Applied Workflow Architecture

Business Intake & Conversational Automation

Haskra Flow

Conversational intake and business workflow automation architecture that connects web and messaging inquiries with structured backend actions—automating FAQ responses, lead qualification, and appointment synchronization.

Technical Scope & Capabilities:

Web & messaging conversational intake and FAQ handling

Automated lead qualification and structured data capture

Webhook and REST API synchronization with CRMs and calendars

Configurable human-in-the-loop escalation routing

Available for Client DeploymentExplore Workflow Deployments

Research Stage • Work in Progress

Foundational Intelligence Layer

Haskra Core

Long-term research and development into specialized reasoning layers and multilingual NLP optimizations designed for regional context and low-latency environments.

Technical Scope & Capabilities:

Multilingual and Afro-centric tokenization research

Lightweight model quantization experiments for constrained hardware

Structured output consistency and evaluation benchmarks

Privacy-conscious data handling architecture

Long-Term R&DView Research Streams

Planned Roadmap

Developer & Orchestration Ecosystem

Haskra Platform

Planned unified orchestration layer aimed at packaging Haskra's internal LLM clients, prompt management, and workflow primitives into reusable developer tooling.

Technical Scope & Capabilities:

Unified TypeScript and Python service wrappers

Centralized prompt template versioning and schema validation

Usage metering, credit accounting, and audit logging primitives

Modular webhook and event-streaming pipelines

Planned InitiativeView Platform Vision

Inside Our Engineering Stack

How We Build: Lessons From Haskra Scholar

When digital agencies or businesses engage Haskra to build a custom AI application, we apply the same decoupled architecture used in Haskra Scholar: a responsive Next.js/React client paired with a type-safe Express/Node.js backend, Prisma/PostgreSQL persistence, structured LLM prompt templates, and real-time Server-Sent Events (SSE) progress updates.

See how we partner with agencies on custom builds

Example Structured Review Output Schema

{
  "overallScore": 84,
  "sectionScores": [
    {
      "section": "Methodology",
      "score": 88,
      "feedback": "Structured evaluation..."
    }
  ],
  "summary": "Compiled synthesis...",
  "generatedAt": "2026-10-28T00:00:00Z"
}

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