One Size Fits None.
The market is flooded with generic AI assistants. They are powerful, but they operate in a vacuum.
- The “Black Box” Problem: They force you to upload data to their cloud, with limited control over retrieval logic.
- The Integration Wall: They might read a PDF, but can they query your legacy SQL database, cross-reference it with a live API, and trigger a workflow in your ERP? Rarely.
- The Fragmented Experience: Your employees end up with 5 different tabs open, trying to piece together information manually.
Our Philosophy: An enterprise AI solution isn’t just a chatbot; it is a sophisticated mix of data engineering, live synchronization, and custom logic.
We Don’t Just Install AI. We Engineer the Entire Pipeline.
Control F5 acts as the architect of your Intelligence Layer.
We combine the best-in-class open-source frameworks, proprietary models or platforms, and custom code to build a solution that fits your specific use case.
What we deliver is a unified system:
Existing Solutions vs. The Control F5 Approach
There are numerous off-the-shelf solutions available that cater to knowledge management. While they offer robust features for general use cases, they often hit a “complexity ceiling” when faced with unique enterprise workflows.
The Control F5 Difference:
We are not a SaaS vendor trying to sell you licenses. We are Development Partners. We take the best components from the market (LLMs, Vector DBs, RAG Solutions) and write the custom glue code that binds them to your specific business logic.
Result: You own the system. You control the data flow. You define the features.
The “Off-the-Shelf” Landscape:
The gold standard for the Office suite, but struggles to index data outside the Microsoft ecosystem or execute complex custom scripts.
Powerful reasoning, but offers limited control over the specific “retrieval” logic needed for highly technical or regulated industries.
Excellent for searching across apps, but comes with high recurring licensing fees and rigid interface options.
Specialized strictly for customer support, lacking the ability to serve as a deep internal “brain” for Ops or Legal teams.
The “Mergers & Acquisitions” Intelligence Engine
- Challenge: A large company acquires a smaller one. Critical operational data is split between two different cloud providers (e.g., Azure vs AWS) and dusty on-premise servers.
- Our Solution: A unified RAG layer that ingests and indexes metadata from both entities without requiring an immediate, massive file migration.
- Custom Feature: A “Conflict Detector” trigger that actively flags if an HR policy found in the acquired company’s documents contradicts the parent company’s master policy handbook.
The Technical Field Assistant (Offline-First)
- Challenge: Field engineers need instant answers about complex machinery schematics while working in remote locations with poor or zero internet connectivity.
- Our Solution: A custom mobile interface optimized for tablets, backed by a “lightweight” local vector database synced daily.
- Custom Feature: Multimodal input allowing engineers to take a photo of a specific machine part and immediately retrieve the relevant repair manual pages and torque specifications.
The Cross-Jurisdictional Contract Engine (Legal & Procurement)
- Challenge: A multinational corporation manages thousands of vendor agreements stored in SharePoint across 20 different countries. Legal teams struggle to identify exposure to new regulations (e.g., GDPR updates or new trade tariffs).
- Our Solution: A RAG system that doesn’t just read the static contracts, but cross-references them against a live feed of regulatory updates via an external legal API.
- Custom Feature: An “Exposure Dashboard” UI that visualizes high-risk vendor contracts on a world map based on real-time legislative changes, triggering automated alerts to local legal counsel.
The Secure R&D “Research Bench” (Pharma & Biotech)
- Challenge: Scientists need to synthesize insights from two highly sensitive sources: proprietary, air-gapped clinical trial data (SQL Databases) and millions of external public medical journals (PDFs/HTML). Standard cloud AI tools are forbidden due to IP leakage risks.
- Our Solution: An on-premise deployment using open-source LLMs (like Llama or Mistral) running entirely within the client’s secure VPC, with zero external data egress.
- Custom Feature: A specialized “Split-Screen” UI designed for researchers, allowing side-by-side comparison of internal trial results vs. published literature, with a mandatory, immutable citation trail for regulatory audit purposes.
The Live Supply Chain Nerve Center (Logistics & Manufacturing)
- Challenge: When an Operations Director asks, “Why is the shipment of microchips delayed?”, a standard RAG tool can only read the static Bill of Lading PDF and say “It was scheduled for Tuesday.” It lacks real-world context.
- Our Solution: A hybrid system that combines RAG on static shipping documents with real-time data ingestion from live APIs (Port Congestion Data, Vessel GPS tracking, and Weather feeds).
Custom Feature: An actionable trigger mechanism: When the AI identifies a high-probability delay based on live data, it automatically calculates alternative routes and pushes a “Proactive Alert” directly into the company’s ERP system (e.g., SAP), prompting the procurement team to adjust production schedules.
🔄 Multi-Source Data Sync
We don’t just upload PDFs. We build live connectors (ETL) for:
- Static Data: PDFs, Word, Excel, scanned images (OCR).
- Live Data: SQL Databases, REST APIs, JSON feeds.
- Third-Party Apps: Salesforce, Jira, Confluence, SharePoint.
- We store this in a centralized, optimized Data Warehouse specialized for AI retrieval.
⚡ Active Triggers & Workflows
Information is useless without action. Our assistants are programmable:
- “If the answer involves a compliance risk, automatically CC the Legal Team.”
- “If the stock level found is low, trigger a draft Purchase Order in the ERP.”
🎨 Fully Custom UI/UX
Forget the standard “chat bubble.” We build interfaces that match your workflow:
- Side-by-side document comparison views.
- Dashboards with analytics on what your employees are searching for.
- Embedded widgets inside your existing intranet.
Q: Will my data be used to train OpenAI/Google models?
A: No. We configure the API/Model with strict data privacy settings. We can even deploy open-source models (like Llama 3) on your own private servers for 100% air-gapped security.
Q: Can it read scanned PDFs (images)?
A: Yes. We include an OCR (Optical Character Recognition) layer that reads scanned documents, diagrams, and handwritten notes.
Q: How long does implementation take?
A: We can launch a functional MVP on your data in 2-3 weeks.
At Control F5, we harness our extensive experience, expertise, and resources to turn your ideas into successful software solutions.