Aporix
AI Agent for Context Optimization
Transform large documents into task-specific LLM context while dramatically reducing token usage, latency, and inference cost. Built for AI agents, developers, and enterprise AI workflows.
Why Context Optimization Matters
LLMs waste tokens on boilerplate, increasing cost and latency while risking context loss. Without optimization, AI applications become slower, more expensive, and less accurate.
High Inference Costs
LLMs charge per token. Long documents with boilerplate, recitals, and repetitive content waste tokens and drive up API costs unnecessarily.
Slow Processing
More tokens means longer processing time. Latency scales linearly with input length, making AI applications feel sluggish and unresponsive.
Lost Context
Important information gets buried in verbose documents. LLMs with limited context windows miss critical facts when documents are too long.
Limited Context Windows
Even the largest context windows have limits. Dense legal, technical, and academic documents often exceed what LLMs can process in a single pass.
From Document to Optimized Context
Aporix analyzes, compresses, and validates documents into task-specific context — ready for any LLM.
Use with any LLM · GPT · Claude · Gemini · Llama
Powered by an Autonomous AI Agent
Aporix is more than a web application. It is deployed as an OpenClaw / ClawUp AI Agent that can autonomously process document optimization requests — accessible via Telegram, web, or MCP.
Telegram Interface
Interact with Aporix directly through Telegram. Send documents and receive optimized context on the go.
Document Analysis
Automatic classification and structural analysis of legal, technical, academic, and business documents.
Optimization Strategy
Goal-driven compression strategies that preserve essential information while removing irrelevant content.
Gemini Integration
Powered by Google Gemini for intelligent document understanding and context-aware optimization.
MCP Server
Model Context Protocol server for seamless integration with AI agents and development tools.
ERC-8004 Registered
Verifiable on-chain identity on GOAT Network. Registered as Agent #83 with provable reputation.
System Architecture
End-to-end architecture showing how documents flow through the Aporix optimization pipeline.
Documents flow through the pipeline and return as optimized, validated context.
Everything You Need
A complete set of tools for document optimization, quality assurance, and cost management.
AI-Powered Optimization
Goal-driven compression that understands document structure and preserves essential information.
Task-Specific Context
Generate context tailored to your specific task — summarization, risk extraction, analysis, and more.
Cost Reduction
Reduce API costs by up to 80% by eliminating unnecessary tokens before they reach the LLM.
Token Savings
Detailed token analytics showing exactly how much you saved and where.
Quality Validation
Built-in confidence scoring and semantic similarity metrics to ensure quality is preserved.
Multi-Document Support
PDF, TXT, JSON, and Markdown — with automatic text extraction and structure analysis.
LLM-Ready Output
Clean, compressed text optimized for direct use with any LLM API.
Fast Processing
Sub-second optimization for most documents, with intelligent caching and parallel processing.
Who Is Aporix For?
From individual developers to enterprise teams — Aporix serves anyone working with LLMs and long documents.
AI Developers
Reduce API costs and improve response times in LLM-powered applications and pipelines.
Legal Teams
Process contracts, agreements, and compliance documents faster with goal-specific extraction.
Researchers
Analyze large academic papers and technical reports without losing critical findings.
Enterprises
Scale AI pipelines across departments with consistent, cost-efficient context optimization.
Students
Optimize study materials, lecture notes, and textbooks for faster comprehension and review.
Real-Time Performance
Aggregate metrics across all document optimizations. Live data will appear as usage grows.
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All time
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Per document
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Total saved
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Per document
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Confidence > 70%
Developer Resources
Everything you need to integrate, extend, and deploy with Aporix.
GitHub Repository
Explore the source code, contribute, and star the project.
API Documentation
Complete API reference for integrating Aporix into your pipeline.
Architecture
Deep dive into the system design and optimization pipeline.
MCP Server
Model Context Protocol server for agent-to-tool communication.
Telegram Agent
Interact with Aporix directly through Telegram.
x402 Payments
Coming soon — pay-per-request with x402 micropayments.
Start Optimizing in Minutes
Choose your interface — web app or Telegram — and start reducing token usage immediately.
Web App
Directly in browser
Upload a document
Drag and drop a PDF, TXT, JSON, or Markdown file.
Choose an optimization goal
Tell Aporix what you need — summarize, extract risks, find key arguments.
Receive optimized context
Get clean, compressed context ready for any LLM.
Telegram
On the go
Start a chat
Open Telegram and message the Aporix bot.
Upload document
Send any supported document directly in chat.
Receive optimized context
Get optimized text delivered instantly.
Send /start to the bot, then upload a document and describe your goal (e.g. "extract key risks" or "summarize this"). The bot runs the full optimization loop and returns compressed output ready to paste into any LLM.
What's Next
Aporix is actively developed. Here's what we've shipped and what's coming.
AI Optimization Pipeline
CompletedCore document analysis and compression engine powered by Gemini.
Web Interface
CompletedFull-featured web application with drag-and-drop, tabs, and analytics.
Telegram Agent
CompletedTelegram bot for on-the-go document optimization.
MCP Server
CompletedModel Context Protocol server for AI agent integration.
ERC-8004 Registration
CompletedOn-chain agent identity on GOAT Network (Agent #83).
x402 Payments
In ProgressPay-per-request micropayments for API access.
Multi-Model Support
PlannedSupport for GPT, Claude, Llama, and other LLM providers.
Enterprise Dashboard
PlannedUsage analytics, team management, and billing.
Batch Optimization
PlannedProcess multiple documents simultaneously.
Collaboration
PlannedShared workspaces and team workflows.
Usage Analytics
PlannedDetailed metrics on token savings, costs, and usage patterns.
Built For Early Adopters
Aporix is designed for AI engineers building LLM applications, developers using RAG pipelines, startups deploying AI agents, legal professionals processing contracts, and researchers working with long documents.
What Users Say
Early feedback from developers and teams using Aporix.
“Aporix reduced our LLM costs by over 70% while maintaining the quality of our extracted insights. The goal-driven compression is a game changer for our legal document pipeline.”
AI Engineer
Enterprise Legal Tech
“We process thousands of academic papers monthly. Aporix helps us cut token usage in half without losing the information we need for our research aggregation platform.”
ML Engineer
Research Platform
“The MCP server integration was seamless. Our AI agents now automatically optimize context before passing it to our reasoning models. The Telegram interface is a nice bonus.”
Founder
AI Agent Startup
Placeholder testimonials — real quotes coming soon.
Frequently Asked Questions
Common questions about Aporix, context optimization, and the agent ecosystem.
Aporix is an AI agent that optimizes documents into task-specific LLM context. It analyzes document structure, removes boilerplate and irrelevant content, and compresses what remains — reducing token usage by up to 80% while preserving goal-relevant information.
Summarization produces a condensed version of the full document. Optimization, by contrast, preserve all goal-relevant facts, dates, names, and obligations while removing only the content that is irrelevant to your specific task. The output is optimized for downstream LLM processing, not human reading.
Aporix is powered by Google Gemini for its optimization pipeline. The output is compatible with any LLM — GPT, Claude, Gemini, Llama, and others. You can use the optimized context with any model or API.
Typical token savings range from 60-80%, depending on the document type and optimization goal. Legal and technical documents with heavy boilerplate see the highest savings. Cost reductions scale linearly with token savings.
Yes! Open t.me/Aporix_optbot, send /start, then upload a document and describe your goal (e.g. "extract key risks" or "summarize this"). The bot runs the full optimization loop and returns compressed output ready for any LLM.
Documents are processed in real-time and are not persisted on our servers. The extracted text is sent to Gemini for optimization and discarded after the response is returned. We do not train on your data.
Aporix supports PDF, TXT, JSON, and Markdown files. PDF text extraction is handled via the pdf-parse library, and all supported formats are converted to clean text before optimization.
Aporix is registered as Agent #83 on GOAT Network's ERC-8004 Identity Registry. This provides verifiable on-chain identity, allowing clients and indexers to discover and trust the agent through a decentralized registry.
Optimize a Document
Upload, set a goal, and get optimized LLM context.