01 AI-First Vision
Goal: 100% of departments supported by AI — from sales and development to HR and finance.
Three Pillars
01
Automation
Eliminate repetitive work. Speed up every process. Cut operating costs.
02
Intelligence
AI analyzes data, suggests decisions, and predicts risks before they happen.
03
Full Coverage
Every department gets its own AI agent — working alongside the team, 24/7.
The formula: AI doesn't replace people — it helps each person work 3–5× more effectively.
02 AI Product Ecosystem
Fabbi both uses AI internally and sells AI commercially — four products, one mission.
FARE
Reads legacy source code (COBOL, Java, PL/SQL) and auto-generates design documents. Helps enterprises modernize decades-old systems.
Saves ~67% cost
NEXA
AI code generation following enterprise SDLC standards. Turns design specs into production code with Japanese-grade quality assurance.
Serving TDC, STNET, HVL
SYNCA
AI-powered quality inspector. Detects bugs automatically, assesses change impact, and enforces quality gates across the entire lifecycle.
VS Code Extension
AIOS
Internal AI Operating System. Each department gets its own agent — understands company data, answers questions, automates reporting.
Internal PlatformEnd-to-End Pipeline
FAREUnderstand old code
→
NEXAGenerate new code
→
SYNCAVerify quality
Analyze → Build → Verify — fully AI-powered
03 AIOS — AI for Every Team
AIOS = AI Operating System. Each department has its own AI agent that understands company data, answers questions, and handles routine work automatically.
How It Works
ConnectERP, CRM, HR…
→
UnderstandAI analyzes
→
ActAuto-report
→
GovernAudit + Policy
Real Examples
- CEO asks: "Q1 revenue vs last year?" — AI answers instantly with ERP data
- HR asks: "Whose contract expires this month?" — AI checks HR system, returns a list
- Sales asks: "Japan pipeline this quarter?" — AI pulls live data from CRM
- Dev asks: "Which bugs block this release?" — AI scans Backlog, answers in seconds
Key strength: AIOS connects multiple data sources (ERP, Backlog, Gmail, Chat) — one question, AI synthesizes from everywhere.
11 Active AI Agents
Each agent serves a specific role — all active, running 24/7.
⭐
BikuruGeneral assistant
live
🧠
Dashboard BODStrategy, KPIs, decisions
live
💰
Finance AgentReports, cost analysis, alerts
live
🎤
Meeting AgentNotes, action items, follow-up
live
👥
HR AgentAttendance, contracts, analytics
live
📋
Presales AgentOpportunities, proposals, estimates
live
🇯🇵
Sales JP AgentJapan pipeline, clients, revenue
live
✅
PQA AgentProcess quality assurance
live
🔧
Tech Lead AgentArchitecture, tech decisions
live
🐛
QA AgentTest cases, bugs, regression
live
📊
PM AgentProgress, risks, weekly reports
live
All agents run on Gemini AI with 200K context and Evolving capability — they learn and improve from Fabbi's own data over time.
04 Where AI Helps — Step by Step
Not vague promises. Here's exactly which agent helps at which step, and what changes.
👨💻 Software Development Workflow
1. Analyze Legacy
AI reads old code, maps dependencies
FARE Agent
→
2. Design Docs
AI auto-generates specs from code
FARE Agent
→
3. Review
Tech Lead reviews AI output
Human + Tech Lead Agent
→
4. Generate Code
AI writes code from approved design
NEXA Agent
→
5. Quality Check
AI detects bugs, measures impact
SYNCA Agent
→
6. Ship
Human approves final release
Step
Before (manual)
After (AI-assisted)
Saved
Analyze legacy code
2 weeks per module
2 days — FARE reads 10K lines/hour
80%
Write design docs
3–5 days per screen
30 min — AI generates, human reviews
90%
Write new code
1 developer × 1 week
NEXA drafts in hours, dev refines
60%
Code review + QA
2 days back-and-forth
SYNCA flags issues instantly
70%
💰 Sales Workflow — From Lead to Proposal
1. Lead Research
AI scans market, scores prospects
Sales JP Agent
→
2. First Contact
Sales rep reaches out
→
3. Discovery
AI prepares questions, analyzes client
Presales Agent
→
4. Proposal
AI drafts estimate + architecture
Presales Agent
→
5. Negotiate
Human closes the deal
Step
Before (manual)
After (AI-assisted)
Saved
Research prospect
1–2 hours Googling
AI delivers brief in 2 min
90%
Create proposal
3–5 days (team effort)
AI draft in 4 hours, human refines
70%
Estimate effort
Senior devs spend half a day
AI generates WBS + estimates
75%
📋 Project Management — Weekly Cycle
1. Collect Data
AI pulls from Backlog, Git, Facon
PM Agent
→
2. Detect Risks
AI flags delays, blockers, scope creep
PM Agent
→
3. Draft Report
AI writes weekly status report
PM Agent
→
4. Review + Send
PM adds insights, sends to client
Step
Before (manual)
After (AI-assisted)
Saved
Gather progress data
45 min checking 5 tools
AI aggregates in real-time
95%
Identify risks
Relies on PM's memory
AI cross-checks timeline vs actual
Better
Write weekly report
1–2 hours every Friday
AI drafts in 30 seconds
95%
👥 HR Operations — Monthly Cycle
1. Attendance
AI syncs check-in data daily
HR Agent · ECS
→
2. Contract Alerts
AI flags expiring contracts 30 days ahead
HR Agent
→
3. Workforce Report
AI shows headcount, turnover, skills gap
HR Agent
→
4. Decide
HR manager acts on AI insights
Step
Before (manual)
After (AI-assisted)
Saved
Check attendance
HR manually checks Excel daily
Auto-synced, anomalies flagged
100%
Contract tracking
Spreadsheet, often missed
AI alerts 30 days before expiry
Zero miss
Monthly HR report
Half day compiling numbers
AI generates on-demand
90%
🎯 Leadership — Decision Making
1. Ask Question
CEO types a question in chat
→
2. Gather Data
AI queries ERP + CRM + HR + Backlog
Dashboard BOD
→
3. Analyze
AI cross-references, finds trends
Dashboard BOD
→
4. Answer
AI replies with numbers + evidence
Dashboard BOD
→
5. Decide
CEO makes informed decision
Step
Before (manual)
After (AI-assisted)
Saved
Get revenue numbers
Ask finance, wait 1–2 days
AI answers in 10 seconds
99%
Compare performance
Someone makes a spreadsheet
AI cross-references 4 data sources
95%
Spot problems early
Only noticed when it's too late
AI alerts proactively
Priceless
The pattern: AI handles steps 1–3 (collect, analyze, draft). Humans handle the final step (decide, approve, act). No department left behind — every workflow gets faster, smarter, more reliable.
05 The Transformation — Before vs. After
Department
Before AI
After AI
Time Saved
Development
Manual coding, manual review, manual testing
AI generates code + reviews + tests
60–90%
Sales
Google prospects, write proposals from scratch
AI researches, drafts proposals, estimates costs
70–90%
Project Mgmt
Check 5 tools, write reports manually every week
AI aggregates + writes reports in 30 seconds
90–95%
HR
Excel tracking, missed contract expirations
Auto-sync, proactive alerts, zero misses
90–100%
Finance
Manual report compilation from multiple systems
AI pulls data, generates reports on-demand
85–95%
Leadership
Wait days for data, decisions based on gut feeling
Ask AI, get evidence-backed answers in seconds
95–99%
Bottom line: What used to take days now takes minutes. What used to be guesswork is now data-driven. What used to fall through the cracks is now automatically tracked.
06 Roadmap
✅ 2024 – 2025
Build Foundation — Develop FARE, NEXA, SYNCA. PoC with Japanese enterprise clients.
🔶 2025 – 2026 · Now
Internal Rollout — AIOS go-live, agents for each department, connect ERP / HR / CRM.
2026 – 2027
Scale Up — AI self-learns from internal data. Proactive predictions. Begin selling AIOS externally.
2028
Full AI-First — 100% of processes AI-assisted. IPO target.
07 Expected Impact
3–5×
Productivity
~67%
Cost Savings
24/7
AI Running
100%
Departments
Impact by Group
For Employees
Less boring tasks, more creative work. AI is your personal assistant.
For Managers
Real-time data, faster decisions, less guessing.
For the Company
Lower costs, higher quality, stronger global competitiveness.
For Clients
Better products, delivered faster, at more reasonable costs.
Core message: AI at Fabbi isn't about replacing people — it's about upgrading them. Every employee gets an AI companion that makes their best work even better.