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Multi-AI Agent for Sales 営業支援マルチAIエージェント

"How did we pitch that client
last year?"

Now you can get an instant answer to that question. A multi-AI agent system where specialized AIs work together across daily reports, deal history, and market information — raising productivity across the sales floor. Start small, then expand step by step as your operations require.

 

Sales rep: Summarize our past proposals to Company X along with the latest competitor trends.
 Multi-AI Agent
 
ActiveSales Report Knowledge
ActiveWeb Search
ExtensionMeeting Minutes
ExtensionOrder Entry
ExtensionProposal Draft

"How did we pitch that client last year?"

Now you can get an instant answer to that question. A multi-AI agent system where specialized AIs work together across daily reports, deal history, and market information — raising productivity across the sales floor. Start small, then expand step by step as your operations require.

Sales rep: Summarize our past proposals to Company X along with the latest competitor trends.
 Multi-AI Agent
 
ActiveSales Report Knowledge
ActiveWeb Search
ExtensionMeeting Minutes
ExtensionOrder Entry
ExtensionProposal Draft

The Challenge

小売DXにあたってのお客様課題

Four Information Challenges Common to Sales Teams

Regardless of industry, the root cause behind lower sales productivity is the same:
information is scattered, impossible to keep track of, and accumulates without ever being put to use.

Data Silo

When a Veteran Rep Transfers, Customer Handling Starts from Scratch

Years of deal history, reasons for lost deals, and each contact's interests exist only in that rep's head.

Buried Data

Reports Get Written, But No One Goes Back to Read Them

Even with daily reports logged in the SFA, finding out "what the client actually wanted" still means asking the rep directly.

Inefficiency

No Time to Research Competitors and Industry Information Before a Meeting

Between visits, travel, and reporting, it's genuinely difficult to also track competitor comparisons and industry trends.

Manual Work

Buried in Order Entry and Paperwork, Proposal Prep Gets Pushed Aside

Some days end with nothing done but routine admin work, leaving less and less time to actually engage with customers.

The Solution

アジアクエストのソリューション

Agents That Scale by "Addition"

Rather than building one giant all-purpose AI, designed as a set of small, specialized AIs,  for each role that connect together and can be added over time.
Start small, then scale to match your operations.

Step 1 | Start Small with the Essential Specialized Agents First

Active

Sales Report Knowledge Agent

Searches and summarizes across SFA/CRM daily reports.

Active

Web Search Agent

Collects and summarizes the latest market and competitor information.

Step 2 Onward | Add Specialized Agents as Operations Require

Extension

Meeting Minutes Agent

Transcribes, summarizes, and extracts action items from sales meetings.

Extension

Order Entry Agent

Automates and assists routine order and form entry.

Extension

Proposal Draft Agent

Generates proposal drafts from past case examples.

Because designed as a set of small, role-specific AIs that connect and can be added over time, you can start with low risk and scale in stages.

Use Cases Use Cases

What It Can Do — Supporting Sales' "Searching, Creating, and Data Entry"

From search, analysis, and summarization to automating proposal prep and admin work — AI supports every phase of sales activity.

Search & Analysis of Reports/Deal History

Answers "What did we propose to this client before?" instantly by searching across daily reports and summarizing.

Win-Pattern & Trend Analysis

Analyzes win/loss trends and surfaces successful patterns and next steps.

On-the-Spot Competitor Comparison/Industry Trends

Collects and summarizes information needed before a meeting from the web — comparison tables of competitor specs/pricing, or the latest trends and challenges in a client's industry.

Meeting Transcription & Summarization

Automatically transcribes sales meeting audio and organizes key points and action items.

Automatic Proposal Outline Generation

Ask "What product best fits this client's challenge?" and it generates solution suggestions and a proposal outline from past reports and market data.

Reduced Order Entry & Admin Work

AI assists with routine order entry and form creation, reducing data-entry burden.

Architecture

システム構成

System Architecture — A Secure Foundation on AWS

Built around Amazon Bedrock, using your own data securely. Data stays entirely within your own AWS environment.

User

User / Administrator

Sales reps and managers ask questions via a chat UI.
Core

Multi-AI Agent

Bedrock Agents orchestrate each specialized AI.
Knowledge

Knowledge Foundation

A Knowledge Base/vector database searches internal company data.
Integration

External Information & Integration

Connects with web search APIs, SFA/CRM, and other data sources.
Data stays entirely within your own AWS environment — it's never used for training, keeping it secure.
Chunking and prompt optimization tune accuracy.
New agents and data sources can be added later.

Value & Benefits 価値とメリット

Value & Benefits — Reclaiming Sales Time and Knowledge

Compresses routine work while raising the quality and speed of proposals — turning "searching, creating, and entering data" time into time spent with customers.

01_impact_time-compress

Compressed Information/Knowledge Search Time

Cross-searching reports and internal materials greatly cuts down time spent hunting for information.

 

Major Reduction in Proposal Prep Effort

AI handles information gathering, competitor comparison, and drafting. Reps focus only on reviewing and refining the content.

 

Better Use of Daily Report/Deal Data

Turns data that used to be "written and forgotten" into a searchable, analyzable asset.

 

Top Performers' Win Patterns Become Team Standards

Analyzing successful patterns and reapplying past proposals turns individual experience into organizational sales capability, lifting the overall win rate.

 

Faster Onboarding for New Hires and Transfers

Quick access to needed information shortens the time to become productive.

 

Sharper, Data-Backed Proposals and Decisions

Supports decisions grounded in accumulated data, not just intuition and experience.

More Than Time Saved: Time that used to go into "searching, researching, and data entry" becomes time spent with clients
— driving continuous improvement in proposal quality and win rate.

Why AsiaQuest アジアクエストが選ばれる理由

Why We're Chosen — A Partner Who Sees It Through to Production

End-to-end support from requirements definition through to production operation and expansion.

01

High Accuracy Tuned to Your Own Data

Delivers answers grounded in your internal reports and knowledge. RAG and tuning are optimized for accuracy fit to your own business context.

02

We Don't Fit Your Operations to an Off-the-Shelf Tool

Rather than conforming to a SaaS product, we fully custom-build and implement solutions around your workflows and data environment.

03

Multi-Agent Design Means Strong Scalability

Start small, then add specialized agents as operations require. Easy to customize, and built to hold up in production.

04

Strong AWS Technical Capability and Track Record

With 400+ engineers and 500+ AWS certifications, we deliver a secure AI foundation built on Bedrock — from requirements definition through internalization support.

How to Start

スタートガイド / はじめ方

Implementation Steps — "Start Small" Then Move to Production

Clear content and deliverables at every phase, from requirements definition to production operation and expansion — advancing step by step with low risk.

STEP 0
1–2 weeks

Assessment & Requirements Definition

Organize current operations, data, and challenges; define target operations, KPIs, and scope.

Requirements definition / KPI design
Most clients start here
STEP 1
1–2 months

PoC / MVP

Measure accuracy using your own data, build a dedicated UI, and verify impact once a baseline level of accuracy is reached. 

MVP environment / Accuracy evaluation report
STEP 2
Ongoing

Accuracy Improvement

Optimize data transformation, chunking, prompts, and model selection.

Tuned model
STEP 3
3–6 months

Full Development

Full multi-agent implementation. Build integration with existing systems and production UI.

Production system
STEP 4
Ongoing

Operation & Expansion

Ongoing operations, maintenance, and accuracy monitoring. Expand to new agents and departments.

Operational structure / Expansion roadmap

Future

今後の展望

Future — From "One Task" to "Company-Wide Intelligence"

The more agents you add, the more internal knowledge accumulates and connects as "usable data," raising productivity across the whole organization.

NOW

Present

Start with specialized agents for the most essential tasks first — sales daily reports, web information, and so on.
SHORT

Short-Term

Add specialized agents for meeting minutes, order entry, and more.
MID

Mid-Term

Expand horizontally to other departments (customer support, marketing, etc.) for company-wide use.
LONG

Long-Term

Agents autonomously coordinate with each other, proactively supporting sales activity.

Ready to Turn Sales Knowledge Into Organizational Strength?

We'll propose a multi-AI agent implementation tailored to your operations and data environment.

Inquiries at the concept stage are also welcome.