Swamped operations queues
Tickets, chats, and emails sorted by hand; slow first response.
→ Agents classify, summarize, and draft next actions with guardrails and escalation.
AI Agent Automation
Custom AI agents & workflow automation
5 weeks to your first AI agent in production
We design, build, and deploy governed AI agents connected to your real systems — with RBAC, audit logs, and human-in-the-loop controls built in.
Get a free automation assessment
We'll identify your top 3 automatable workflows — in 48 hours.
200+ Engineers·9+ Years·ISO 27001·AWS Partner
How a governed workflow runs
1
Request comes in
2
Agent processes
3
Human approves
4
Task completed
Trusted across industries
Logistics · JapanFMCG · VietnamFinTech · SingaporeManufacturing · GermanyIT Services · VietnamRetail · Japan
Pain → outcome
Less manual work, more control
Automation should reduce busywork—not create new blind spots. Here is what we commonly replace with agents plus governance.
Reporting and document churn
Copy-paste between spreadsheets, slide decks, and internal wikis.
→ Scheduled agents pull sources, generate drafts, and notify owners for approval.
Fragile AI experiments
One-off prompts with no ownership, logging, or production path.
→ Versioned prompts/policies, test harnesses, and monitored runs with measurable KPIs.
Case studies
Where agent automation delivers results
Three production examples from teams that moved from manual bottlenecks to governed agent workflows.
-97% response time
Customer Support Triage Agent
A mid-size logistics company in Osaka with 15 CS agents handling 1,200 tickets/month. We built a 3-layer AI agent system: auto-triage into 8 categories, auto-response for common queries by connecting to their TMS, and smart escalation for complex issues. Full audit logging and RBAC included.
6hr → 4min response42% auto-resolvedCSAT 3.2 → 4.4Cost/ticket -55%
5 weeks to production
Read full story →5x faster processing
Document Processing & Compliance Agent
A food manufacturer exporting to Japan, Singapore, and Germany processed 80-120 document sets monthly. We built an AI pipeline: OCR extraction (Vietnamese/English/Japanese), cross-document validation, and market-specific compliance checking. When regulations change, only the knowledge base needs updating — no redeployment.
4hr → 45min per setErrors 12% → 2%Customs delays -80%Throughput +167%
7 weeks to production
Read full story →-60% onboarding time
Internal Knowledge & Onboarding Agent
A 200-engineer IT company with knowledge scattered across Confluence, Google Drive, and Slack. We built a knowledge agent that indexes all sources with proper access controls, answers questions in Vietnamese or English with source citations, auto-generates onboarding paths, and detects knowledge gaps for team leads to fill.
3wk → 1.2wk onboardSenior eng. time -75%68% auto-answeredSatisfaction +35%
5 weeks to production
Read full story →WHAT CLIENTS SAY
Haposoft's team delivered our first agent in 4 weeks — faster than our internal team estimated. The governance controls gave our CTO confidence to approve production deployment.
TK
— Tanaka K., VP of Operations, Logistics company (Osaka)
What surprised us was how well they understood our compliance requirements. The agent handles three languages and three different regulatory frameworks — and it just works.
NM
— Nguyen M., Export Director, FMCG manufacturer (HCMC)
We calculated ROI at month 3. The agent handles 42% of tickets without human intervention. Our support team now focuses on complex cases instead of copy-pasting tracking numbers.
ST
— Suzuki T., CS Manager, Mid-size logistics company (Japan)
READINESS CHECK
Is your workflow ready for AI agents?
Answer 4 quick questions — no email required
Step 1 of 4
What type of work do you want to automate?
Your answers are not stored or shared.
How we work
From idea to running agents
A predictable path so business, IT, and security stay aligned.
1
Discover
Workflow & stakeholder map
We anchor on one workflow, its data sources, and who must approve what.
2
Design
Agent + policy design
Tool permissions, retrieval boundaries, refusal modes, and human stops are explicit.
3
Build
Build and connect
We implement agents, integrations, and guardrails against your real data and system flows.
4
Deploy
Go live with controls
Rollout starts with scoped approvals, observability, and escalation paths ready from day one.
5
Govern
Improve continuously
We tune workflows with real feedback while preserving auditability and policy alignment.
Typical timeline: 5-8 weeks to first agent in production.
Pilot engagements start from $15,000.
MCP · Model Context Protocol
Connect AI agents to your systems through MCP, not one-off integrations
Model Context Protocol (MCP) is an open standard that lets AI assistants such as Claude and ChatGPT read from and act in business software. Each system exposes an MCP server that compatible assistants can use. Client support is set per product. Haposoft builds that server for your system as part of the project.
What MCP is
An open standard for connecting AI assistants to tools and data. A system publishes what an agent may read and do as a list of tools, and the assistant calls them.
Why it beats point-to-point integrations
Without a shared protocol, every assistant and system pair needs its own custom connector. With MCP, one server per system can work with any compatible assistant we enable it for, so adding or switching assistants does not mean rebuilding the integration.
What Haposoft builds
We design and build the MCP server for your ERP, CRM, internal tool or legacy system, agree with you which tools exist, and wire in sign-in, permissions and logging.
Built so the agent stays inside the rules
- The agent acts with the signed-in user's own permissions, never broader.
- Write actions are recorded in the audit log, and denied requests are logged.
- Write actions are confirmed by the user in the AI client or switched on separately.
- Tools are chosen per project. Actions such as approving, grading or deleting can be left out entirely.
Already available in Haposoft products
Claude and ChatGPT
OKR Management (Hapo OKR)
Hapo OKR runs an MCP server with Google sign-in. Assistants can read objectives and progress and, with confirmation, post check-ins, comments and action items or draft objectives and key results. Approving, grading and deleting are not exposed.
OKR Management (Hapo OKR)Claude
Sales Management (Hapo SMS)
Hapo SMS has an MCP connector for Claude. It reads CRM data and can create contacts, notes and tasks within the user's permissions, with rate limits and logged denials.
Sales Management (Hapo SMS)Our other products and your existing systems do not have an MCP server today. We can build one for them inside your project, scoped and agreed upfront.
Talk to us about an MCP serverAgents vs. a basic chatbot
Both can answer questions. Only governed agents can execute real workflows across your systems with clear controls.
| Capability | Basic chatbot | Haposoft Agent |
|---|---|---|
| Setup | Pre-built template | Custom-built for your workflow |
| Data access | FAQ / knowledge base only | Connected to your systems (ERP, CRM, databases) |
| Decision making | If/then rules | Context-aware AI reasoning |
| Audit trail | Basic logs | Full audit log with RBAC |
| Human override | None | Human-in-the-loop at any step + kill switch |
| Learning | Manual updates | Continuous improvement from feedback |
FAQ
Questions we hear in every first call
Clear answers your stakeholders usually ask before greenlighting a pilot.
Chatbots answer from a script. Our agents connect to your real systems, make context-aware decisions, and operate under governance controls (RBAC, audit logs, human-in-the-loop). Think of it as the difference between a FAQ page and a trained team member.
First agent in production within 5-8 weeks. Most clients see measurable ROI by month 3-4 — typically through time saved or errors reduced.
Pilot engagements start from $15,000 for a single workflow. Scale depends on complexity, integrations, and number of agents. We scope and quote after a free 48-hour assessment.
We're ISO 27001 certified. Agents run on your infrastructure or a dedicated cloud instance — never shared tenancy. All data processing follows your existing compliance policies.
Our 48-hour assessment is free — you'll receive a written report of your top 3 automatable workflows whether you work with us or not. For paid engagements, we define success KPIs upfront. If your first agent doesn't reach production within the agreed timeline, we extend the engagement at no additional cost.
Every agent ships with human-in-the-loop approval, a kill switch, and full audit logging. You're always in control. Agents flag uncertainty instead of guessing.
OpenAI, Anthropic Claude, AWS Bedrock, Azure OpenAI — or on-premise models if you need it. We're cloud-agnostic and integrate with your existing stack.
MCP (Model Context Protocol) is an open standard for connecting AI assistants to business software. Each system publishes one MCP server that lists what an agent may read and do, and compatible assistants can use it. Client support is set per product: Hapo OKR works with Claude and ChatGPT, and Hapo SMS with Claude. That avoids building a separate custom connector for every agent and system pair. Haposoft builds the MCP server for your system as part of the project.
No. By design, the agent acts only within the signed-in user's own permissions and cannot reach what that user cannot. Write actions are recorded in the audit log, denied requests are logged, and write actions are either confirmed by the user in the AI client or switched on separately. We also leave out actions you never want automated, such as approving, grading or deleting records.
Ready to automate with agents you can govern?
Tell us your workflow. We'll show you what an agent can do — free assessment in 48 hours.
ISO 27001AWS Select Partner200+ Engineers
Free 48-hour assessment · No commitment required · Written report included