AGENTIC SYSTEMS
Chemical Regulations Breaks Barriers With AI Agents
A major chemical regulations firm serving major brands across America and Europe collaborated with Antematter to tackle critical barriers in their sales and operations workflows using AI agents.
Our Client
Our client operates at the intersection of environmental health and safety (EHS)
Core Challenges
The client’s growth trajectory faced two key operational constraints:
Language Barriers
Their sales department provides services in 11 languages but encountered systematic communication breakdowns during client interactions. These language barriers became particularly acute given our client’s extensive international operations across Asia-Pacific, European and Latin American markets where regulatory frameworks vary and real-time technical consultation requires nuanced understanding of local compliance requirements. Sales representatives frequently lacked access to necessary context during live calls, forcing multiple follow-ups to provide essential regulatory intelligence.
Language Barriers
Their Solutions Engineering team experiences severe inefficiencies in RFP completion workflows. Each proposal, typically containing 50-100 technical questions, required up to 32 hours of manual, cross-departmental labour, limiting their ability to pursue concurrent opportunities, and imposing substantial operational overheads.
Solution Overview
Antematter developed a dual-component solution, leveraging fine-tuned OSS models with complete data privacy controls:
Realtime translation platform (RTT)
Delivers on-device multi-lingual translation through a sequential processing pipeline with sub-3-second response latency across the entire process. The system combines OpenAI’s Whisper-v3 for STT and Qwen2.5-7b-Instruct for bidirectional translations and contextual suggestions, paired with MeloTTS for final audio synthesis.
RFP Automation System
Automates proposal workflows through intelligent document processing and collaborative answer generation. The platform uses Qwen2.5-7b models for query extraction paired with FAISS vector search grounded in a 6,000 node knowledge graph.
The RFP platform has a prompt-first architecture, eliminating reliance on agent complexities through handcrafted prompts leveraging Chain-of-Thought, Three-of-Thought, Monte-Carlo Simulations and so on. CAG (cache-augmented generation) in conjunction with RAG (retrieval augmented generation) were used allowing for low-latency inference.
The system is integrated with Okta and RBAC to enable secure multi-user collaboration across multiple document formats.
Solution Description
Our solutions integrate seamlessly into their existing operational infrastructure while maintaining all security requirements through self-hostable deployment frameworks.
The RFP platform deployed across three LambdaLabs A40 instances (DEV/BETA/PROD), with Azure CI/CD pipelines managing version control and deployment automation. Our architecture separated frontend UI, request management, and Python LLM API layers, with all communication routing through the backend to two llama.cpp servers running Qwen2.5 models.
The RTT system, facing deployment issues as-is, evolved into a streamlined translation API utilizing LiteLLM routing to SambaNova’s Qwen3-32B model, delivering accelerated generation speeds through pre-defined translation prompts. FAISS implementation achieved sub-600-millisecond query response times while maintaining regulatory compliance through knowledge graph retention.
Operational Impact
The delivered solution yielded the following immediate outcomes:
RFP Processing Transformation
Completion time for each process reduced from 32-hours to 10-15 minutes per proposal - a 95% decrease in operational resources required. The Solutions Engineering team successfully transitioned from a 4-day turn around to same-day proposal.
Translation Infrastructure
While the RTT system faced deployment constraints, the real-time translation capabilities were successfully repurposed into a centralized API platform, supporting developer tooling across text, audio and image-based modalities.
Collaborative Efficiency
RFP platform’s RBAC and real-time editing capabilities eliminated cross-departmental co-ordination bottleneck through sub-600-millisecond query responses.
Strategic Outcomes
Our client was able to expand their automation capabilities to encompass new document classes and client-facing communication systems. The Solution Engineering team saves 29-30 hours per proposal while maintaining specialized technical quality standards with their clients.
The foundations established through Antematter’s solutions position our client to scale their global compliance services without bottlenecks in operations.
