AI Applications
Custom AI-powered applications, built around your business workflows.
Talk to us about an AI applicationYour business isn't generic. Your AI shouldn't be either.
Off-the-shelf AI tools solve general problems. Your hardest problems are specific — and that's exactly where generic tools fall short. AAXIS builds AI applications around the way your business actually works: purpose-built tools and interfaces that put AI to work on a defined job, designed around your workflows rather than bought to fit them. The result is production software your team owns and uses directly — not a model you're left to figure out how to apply.
The shift is already underway. The question is no longer whether to put AI in front of your customers and teams — it's which workflow to start with.
67%
of B2B buyers now prefer a rep-free, self-service buying experience
Gartner, 2026
~30%
of a rep's time is actually spent selling
Salesforce
WHY AAXIS
Why AAXIS
Agentic conversational commerce & product discovery
The problem
- Customers still call or email for a quote, orders leak when no one picks up, and buyers can't find the exact product fast across deep, technical catalogs.
Solutions
- A voice-and-chat agent that handles product discovery and ordering in plain language — hybrid, semantic, and visual search across large catalogs, SKU-level recommendations, and a copilot that turns a question into the right filters, explains attributes, and answers spec-level questions from indexed product knowledge.
Customer service voice & chat agent
The problem
- At peak hours, phone traffic exceeds the team's bandwidth and a quarter of inbound calls go unanswered, while reps lose time verifying identity and intent across disconnected systems.
The solution
- Voice and SMS agents that capture every inbound contact, extract customer identity and order detail automatically, and rank tickets so urgent, high-value orders reach a rep first — turning interruptions into prioritized, context-rich work.
Call quality & compliance agent
The problem
- Organizations handle thousands of interactions a day, and manual review reaches only a small sample — leaving most calls unmonitored for service quality, compliance, and policy adherence.
The solution
- An agent that analyzes calls and conversations at scale, detects compliance, policy, and ethical violations, flags escalation risk, and generates call summaries and coaching recommendations — turning spot-check auditing into full coverage.
Sales & deal support agent
The problem
- Inbound email volume buries opportunities, manual deal entry is slow and error-prone, and long threads are hard to act on.
The solution
- An agent that monitors the inbox, tags and detects opportunities, extracts and imports deals from files, summarizes threads with clear next steps, and drafts context-aware, tone-matched replies — so reps spend their time selling, not sorting.
Sales enablement agent
The problem
- Reps spend more time hunting for product information and customer history than engaging customers.
The solution
- A rep-facing copilot with instant access to product knowledge, account and order-history insights, cross-sell and upsell recommendations, and guided product comparisons — so reps focus on the customer, not the lookup.
Product information intelligence
The problem
- Critical product data is scattered across millions of technical documents, safety data sheets, lab reports, and regulatory files.
The solution
- An agent that extracts specifications and attributes from technical and regulatory documents, normalizes and enriches the data, and assembles a centralized product information master with continuous catalog governance — building on our B2B Product Intelligence work.
Production support agent
The problem
- Routine technical support — cache refreshes, SKU indexing, SEO redirects, server restarts, build and monitoring checks — pulls engineers off higher-value work.
The solution
- An agentic support assistant that coordinates specialized agents across enterprise systems, applies role and privilege governance for safe access, and performs these tasks expeditiously with context-aware assistance throughout.
How we deliver
The build
- Application and experience design, a build on the stack above, and integration to your data and the systems that hold it.
- AI-assisted development compresses the timeline, so a working application reaches your teams faster than a traditional build.
- Data preparation is scoped into the work rather than treated as a prerequisite that stalls the project.
The deliverable
- A production application with AI built in, owned and operated by you, solving a defined problem end to end.
- Not a prototype, not a slide — a tool your teams open and use, running on a foundation you can build the next application on.
How it's built
- AI Foundation
The models and infrastructure every application runs on — language, speech, and vision models, served on cloud you already use. LLMs (GPT, Gemini, Qwen), speech-to-text and text-to-speech, embedding models, on GCP, Azure, or AWS.
- Knowledge Layer
Turns fragmented enterprise knowledge into something AI can reason over, so the right answer surfaces regardless of who's at their desk. Retrieval-augmented generation (RAG), knowledge graphs, and vector, document, and conversation stores.
- Agent Orchestration
Coordinates multiple specialized agents and the tools they call, so a request flows across systems instead of stopping at one. LangChain and LangGraph, the Model Context Protocol (MCP), with tracing, logging, and evaluation built in.
- Experience & Application
The interface your teams and customers actually use — web, voice, or chat — built on a modern, fast front end. React and Next.js front ends, FastAPI services, voice and chat channels wired to the agents beneath.
- Governance & Security
The controls that make autonomous software safe to run — across every layer, not bolted on at the end. Identity and access control, human-in-the-loop review, content moderation, guardrails, and an immutable audit log.
Representative engagements, in production
Custom AI applications built around a specific operational workflow and put into production. Figures below are industry benchmarks for comparable deployments; AAXIS client-specific results are available under NDA
Conversational Commerce & Product Discovery — HVAC Distribution
Challenge
- •Customers depended on support reps for product detail, inventory, order history, and purchasing.
- •Two-thirds of B2B buyers now prefer to self-serve rather than call in.
Solution
- •Voice-and-chat commerce agent for product discovery and intelligent search.
- •Inventory and order-status inquiries across locations.
- •Cart creation and order placement in plain language.
- •Personalized recommendations by account and history.
Outcome
- •AI self-service deflects 40–60% of routine inquiries from the support center.
- •Recovers orders that used to leak when no one picked up — turning the support line into a sales channel.
40 - 60%
of routine inquiries deflected
Voice + chat
one agent across both channels
Real-time
inventory & order-status answers
Built for HVAC
distributors specifically
CALL QUALITY & COMPLIANCE
High-volume customer service
An agent that analyzes 100% of calls and conversations, detects compliance and policy violations, and generates coaching recommendations — coverage moves from a spot-check sample to every interaction.
SALES ENABLEMENT
Distribution sales teams
A rep-facing copilot with product knowledge, account history, and cross-sell guidance at hand — recovering non-selling time is the single biggest lever on rep productivity and pipeline.
PRODUCT INFORMATION INTELLIGENCE
Chemical manufacturing
An agent that extracts specs from technical and regulatory documents. Content prep drops from ~20 minutes per SKU to ~2 (≈90% faster), and automated routing cuts errors up to 95%.
AI Applications FAQs
See how AAXIS helps your platform
Off-the-shelf tools solve general problems. AI Applications are built around your specific workflow and data on a stack we assemble — foundation, knowledge, orchestration, experience — so they fit the job exactly rather than forcing your process to fit the tool.
Concrete things we build: handle product discovery and ordering over voice and chat, answer support calls and prioritize the urgent ones, monitor calls for quality and compliance at scale, monitor the sales inbox and draft replies, arm reps with product knowledge and account history, turn scattered technical documents into clean product data, and run routine production-support tasks across your systems — each measured against the cost or revenue it moves.
Governance and security are a layer of the stack, not an afterthought. Applications run on the cloud you already use with identity and access controls, content moderation, and an immutable audit log. Answers are grounded in your own indexed knowledge through retrieval-augmented generation — so the agent works from your data rather than guessing — with human-in-the-loop review on sensitive actions.
No. We start with one high-value application. Because the foundation, knowledge, and orchestration layers are reusable, each application after the first costs less and ships faster — the stack compounds rather than starting over.
Where this work gets done
Building Materials
Streamlining operations through enterprise digital services and automation.
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