AI-Native Delivery for Speed and Quality
We combine AI consulting experience, in-house product know-how, and AI-assisted engineering to deliver faster without sacrificing quality.
Why Our AI Delivery Is Faster
We use AI across planning, implementation, testing, and operations with proven patterns from real projects.
AI-enabled delivery ratio
90%+
We embed AI in planning, coding, test design, and documentation workflows.
Fastest launch
1 month
Clear MVP scope projects can be shipped in about one month.
Delivery efficiency
Up to 2.5x
Reusable patterns and in-house AI know-how improve implementation velocity.
Quality control
Standardized
Code review, automated tests, and monitoring are mandatory steps.
Execution Know-how from In-house AI Products
We transfer lessons from building and operating our own AI products to client delivery.
- Real incident patterns and fixes are integrated into delivery templates.
- Performance, cost, and quality are optimized together.
- Proven architecture shortens the design phase.
Strong AI Consulting Track Record
We design for adoption, not just PoC completion, with business and governance alignment.
- We prioritize use cases by ROI and feasibility.
- We include governance and security in the rollout plan.
- We support training and operational onboarding.
AI-Integrated Engineering Process
We run AI-assisted delivery from requirements to testing with clear quality gates.
- AI-assisted implementation and test-case design are standardized.
- E2E tests and observability maintain release quality.
- Short feedback cycles improve post-release outcomes.
Launch in 1 Month from JPY 6M
For clear MVP scopes, we can deliver from design to release in one month and support the first growth cycle after launch.
AI-Driven Development Services
Our delivery model improves speed, quality, and cost efficiency at the same time.
React / Next.js Web Development
We deliver B2B/B2C web products end-to-end, from architecture to operations, with KPI-driven design and maintainable implementation.
We define UI, API, and operation requirements together before development to reduce rework and speed up delivery.
After launch, we keep improving conversion, speed, and retention through measurable iteration.
Key Scope
- Next.js (App Router) / React / TypeScript implementation
- Admin panel, account system, and payment integrations
- SEO and Core Web Vitals optimization
- Review, testing, and delivery standardization
iPhone App Development (Swift / SwiftUI)
We build high-quality iPhone apps from requirement design to App Store release and continuous improvement.
We optimize native UX, offline behavior, and API integration based on real usage patterns.
We support quality control and release management with crash analysis and retention metrics.
Key Scope
- Swift / SwiftUI app development and refactoring
- Auth, payment, push, location, and camera integration
- API design and backend collaboration
- TestFlight operation and App Store submission support
AI Consulting and Adoption Support
We support AI adoption from use-case discovery to rollout so organizations can move from PoC to production.
We prioritize AI initiatives by ROI and feasibility to avoid over-scoped projects.
We design governance, security, and operation models for practical company-wide adoption.
Key Scope
- AI roadmap planning and prioritization
- Prompt design and governance policy development
- PoC design and measurable validation setup
- Operational onboarding and internal enablement
AI System Development
We implement production-grade AI systems integrated with existing workflows, not standalone demos.
We build RAG, workflow automation, and data integrations with access control and auditability.
We optimize not only model quality but also latency, cost, and operational reliability.
Key Scope
- RAG and internal knowledge assistant implementation
- Document generation, review, and classification automation
- Enterprise API integration and workflow orchestration
- Monitoring, audit logging, and cost optimization
Why Clients Choose Us
We provide practical execution backed by AI product operations and consulting outcomes.
KPI-First Architecture
We design systems backward from business KPIs such as conversion, retention, and operational efficiency.
- KPI-to-feature mapping is defined at project start.
- Measurement and dashboard setup are included in implementation.
- Prioritization is based on expected impact.
Implementation-Ready Requirement Definition
We define screens, data structures, and operational flow before coding starts.
- UI and API specs are created together.
- Exception handling and role-based scenarios are documented.
- Future extensibility is considered in domain design.
Speed with Reliable Quality
Fast iteration is combined with review, testing, and monitoring standards.
- Weekly release planning with clear ownership.
- Design and code review checklists are standardized.
- Root-cause and prevention flow is part of operations.
Adoption-Focused Delivery
We support training and handover so solutions are used in day-to-day operations.
- Administrator and end-user guides are prepared.
- Initial operational support and Q&A process are set up.
- Improvement backlog is reviewed in regular sessions.
Delivery Process
We show both common market timelines and our AI-accelerated delivery speed.
Phase 01
Current-State Assessment
Market average: 2-4 weeks
Our speed: 3-5 business days
Analyze systems, workflows, and data quality to define priority issues.
- Assessment report
- Prioritized issue list
- Initial roadmap
Phase 02
Requirements and Design
Market average: 3-6 weeks
Our speed: 1-2 weeks
Define functional and non-functional requirements with operation design.
- Requirement spec
- UI/API/data design
- Test strategy
Phase 03
Prototype / PoC
Market average: 3-5 weeks
Our speed: around 1 week
Validate high-risk assumptions and lock implementation direction.
- Prototype
- Technical decision log
- PoC evaluation
Phase 04
Build and QA
Market average: 12-24 weeks
Our speed: 4-12 weeks
Implement in short cycles with quality gates through review and tests.
- Production-ready application
- Test suite
- Monitoring setup
Phase 05
Release and Enablement
Market average: 2-4 weeks
Our speed: 3-7 business days
Plan launch, train teams, and establish operation procedures.
- Release plan
- Operation manuals
- Support workflow
Phase 06
Continuous Improvement
Market average: monthly cycle
Our speed: weekly cycle
Run KPI reviews and prioritize ongoing enhancements.
- KPI report
- Improvement backlog
- Quarterly roadmap
Timeline varies by complexity, external integrations, and approval flow.
Sample Timeline & Budget Plans
These are representative plans. We start from 1-month / JPY 6M for clear MVP projects.
Fast Launch
MVP / small-to-mid business app
Focus on core features and release quickly to validate market response.
From 1 month
From JPY 6,000,000 (excl. tax)
PM x1 / Full-stack x2 / AI+QA x1
- Intensive requirement workshop
- Core flows implementation
- Auth, admin panel, analytics setup
- Launch support and initial operation guide
Growth Delivery
Service refresh / mid-scale expansion
Modernize existing assets while improving architecture and operations.
Around 3 months
JPY 12,000,000-20,000,000 (excl. tax)
PM x1 / Frontend x2 / Backend x2 / QA x1
- System assessment and migration plan
- UI/API redesign and operational improvements
- E2E test and monitoring setup
- Improvement cycle enablement
Enterprise Program
Large multi-department delivery
Roll out in phases with governance and security controls for enterprise scale.
Around 6 months
JPY 30,000,000-60,000,000 (excl. tax)
Program PM x1 / Tech lead x1 / Engineers x4-6 / QA x2 / AI consultant x1
- Enterprise architecture and phased rollout design
- Audit log and permission control implementation
- Cross-team training and governance setup
- Post-launch optimization roadmap
These are rough estimates for initial planning. Infrastructure and third-party costs are excluded.
Quality, Security, and Operational Readiness
We standardize quality and governance so teams can scale after launch.
Quality Assurance
Unit, integration, and E2E tests are built into delivery from the beginning.
Security
Access control, audit logs, and vulnerability management are standardized.
Operational Monitoring
Alert thresholds and incident response runbooks are prepared before release.
Cost Optimization
Cloud cost and performance are continuously monitored and optimized.
Documentation
Design decisions and operation procedures are kept maintainable for handover.
Improvement Management
KPI-based reviews drive prioritization and ongoing feature refinement.
Case Studies
Three examples for each service line to show practical delivery outcomes.
React / Next.js Development Cases
Three examples of web product delivery and modernization.
B2B Order SaaS Frontend Redesign
Trading SaaS Company
Unified ordering workflow and reduced manual processing time.
Challenges
- Complex UI flow
- Frequent input errors
Approach
- Workflow-driven UI redesign
- Type-safe form architecture
Results
- 42% faster input
- 35% fewer inquiries
Tech Stack
E-commerce Performance Optimization
D2C Brand
Improved page speed and conversion during campaign peaks.
Challenges
- Slow mobile pages
- Limited analytics
Approach
- Rendering optimization
- Measurement redesign
Results
- LCP improved to 1.7s
- 1.6x mobile CVR
Tech Stack
Legacy Portal Modernization
Education Service Company
Migrated legacy modules without downtime.
Challenges
- No downtime requirement
- Data consistency
Approach
- Phased migration
- Operational automation
Results
- Zero downtime migration
- 55% less manual operation
Tech Stack
iPhone App Development Cases
Examples across field operations, EdTech, and healthcare.
Field Work Reporting App
Maintenance Service Company
Digitized reporting and reduced back-office workload.
Challenges
- Paper-based operations
- Input quality issues
Approach
- Offline-first mobile flow
- Photo/location integration
Results
- 50% faster reporting
- Defect rate dropped to 6%
Tech Stack
Learning App Retention Improvement
EdTech Provider
Redesigned onboarding and notifications for retention growth.
Challenges
- Low retention
- Unclear user behavior
Approach
- Onboarding redesign
- Segmented push strategy
Results
- 1.4x 7-day retention
- 41% push open rate
Tech Stack
Medical Device Connectivity App
HealthTech Company
Stabilized BLE connectivity and data synchronization.
Challenges
- Unstable reconnection
- Data gaps
Approach
- Connection state machine
- Retry-safe sync design
Results
- Data loss reduced to 0.08%
- 40% crash reduction
Tech Stack
AI Consulting Cases
From roadmap design to organizational adoption.
Call Center AI Roadmap
BPO Company
Defined practical use-case priority and rollout phases.
Challenges
- Too many use cases
- Unclear investment basis
Approach
- Log analysis
- ROI + feasibility prioritization
Results
- 8 priority areas selected
- Approved implementation budget
Tech Stack
AI Enablement for Sales Team
SaaS Company
Standardized proposal and meeting-summary generation workflow.
Challenges
- Inconsistent output quality
- Security concerns
Approach
- Prompt templates
- Governance policy design
Results
- 38% less prep time
- 80%+ adoption in 3 months
Tech Stack
Back-office AI Opportunity Assessment
Mid-size Manufacturer
Defined practical AI initiatives for HR, legal, and finance.
Challenges
- Cross-team process differences
- No AI owner
Approach
- Process mapping
- 90-day rollout planning
Results
- 60% of target workstreams planned
- AI governance team launched
Tech Stack
AI System Development Cases
Production-grade AI implementation across multiple business workflows.
Enterprise Knowledge Search Platform
IT Service Company
Built RAG-based search with access control and monitoring.
Challenges
- Scattered documents
- Low search success rate
Approach
- Index pipeline
- Metadata and permission design
Results
- 29% fewer internal inquiries
- 45% faster information lookup
Tech Stack
Contract Review Assistant
Listed Enterprise
Automated first-pass review with legal team governance.
Challenges
- Review bottlenecks
- Rule inconsistency
Approach
- Clause classification
- Human-in-the-loop workflow
Results
- 52% faster first review
- Better quality consistency
Tech Stack
Support Ticket Classification & Reply Drafting
E-commerce Company
Automated ticket routing and suggested responses for agents.
Challenges
- Slow response in peak periods
- Quality variance
Approach
- Priority classifier
- Reply draft and approval flow
Results
- 46% faster first response
- 18% fewer repeat inquiries
Tech Stack