Platform Architecture Overview

Fast Forward is built from the ground up to give IT teams full control over intelligent automation — combining the flexibility of large language models (LLMs) with a governed execution layer that’s safe, adaptable, and fully extensible.

At the Core: LLM-Powered Intelligence

At the heart of every agent is a large language model (LLM), providing reasoning, natural language understanding, and conversational handling. Fast Forward uses a fully private, GDPR-compliant LLM setup — ensuring that no proprietary or sensitive data ever leaks. The model runs in a controlled environment, with complete isolation from public LLMs.

The Agentic Shell (Configurable Execution Layer)

Our proprietary Agentic Shell orchestrates agent behavior. It manages tool selection, memory usage, self-reflection, and reasoning cycles. The shell is configurable, allowing IT to define how agents reason, what safety measures apply, and how decisions are logged and reviewed.

Supports custom workflows and skill chaining

Integrates with the MCP (Model Context Protocol)

Fully controllable through configuration files or admin console

Agent Toolkit: Python-Based Action Layer

Agents use a growing library of Python-based tools to interact with applications, APIs, and file systems. These tools are functionally similar to RPA actions — but designed for modern, AI-driven task execution.

  • Tools can be generic (e.g., sending emails, manipulating Excel files) or custom-developed
  • All executions are traceable and logged for compliance and debugging
  • Tools can be developed in-house, by partners, or by us using the Fast Forward Toolmaking Toolkit

Embedded Python Interpreter

Each agent includes access to an isolated Python interpreter. This enables agents to perform logic-heavy operations, advanced data processing, or dynamic scripting — whether based on user prompts or their own task plans.

  • Ideal for real-time data analysis, transformations, or conditional flows
  • Supports both static (pre-approved) and dynamically generated code

Skill Evolution and Memory

Agents improve over time. Through daily use, they learn from feedback and adjust how and when they use specific tools. Skills evolve as patterns emerge in task execution, making agents more effective and context-aware.

Short-term memory helps manage conversations and sessions

Long-term memory (via RAG) enables agents to refer to previous work, internal documents, or user preferences

Skills are versioned, tested, and subject to IT governance

Full On-Premise Deployment Option

The entire Fast Forward platform — including LLM, agent shell, memory, tools, and interface — can be deployed entirely on premise. This enables organizations with strict regulatory or data sovereignty requirements to retain full control.

ROI and Usage Monitoring

All agent activity is tracked in a centralized online management dashboard. IT and business owners can monitor usage, identify high-value automations, and track real-world ROI. The dashboard offers transparency into agent performance, tool usage, and adoption metrics.