We design, build, and operate AI systems that do real work inside your company — with clearly defined boundaries of responsibility and data that stays in your hands.
| System | Function |
|---|---|
| AI Customer Service | Answers product questions, handles complaints, triages incoming tickets, and escalates to a human with the full conversation context attached |
| AI Sales & Lead Handling | Qualifies leads, answers pricing and specification questions, schedules meetings, and runs ongoing follow-up |
| Voice & Messaging Agent | Agents on phone and messaging channels: orders, bookings, status checks, and reminders — in Indonesian and English |
| Knowledge Copilot | SOPs, contracts, and ticket history become an internal assistant that answers with citations back to the source documents |
| Document & Back-office Automation | Preparation and reconciliation of invoices, purchase orders, claim forms, and recurring reporting |
| Private LLM Deployment | Models run on your own infrastructure, including environments with no outbound access |
Workflows outside this list can still be discussed. If the process and the desired outcome can be described, we will tell you honestly whether AI is the right tool — including when the answer is that it is not.
Mapping the workflow, the available data, the systems that must be integrated, and a measurable definition of success.
An initial version testable against real data — small enough to discard, real enough to evaluate.
Integration with your systems, human escalation handling, logging, recurring evaluation, and access controls.
Monitoring answer quality, tuning based on real cases, and updates as requirements change.
| Model | Description |
|---|---|
| Sovereign cloud | Runs on infrastructure within your jurisdiction, with no data replication to other regions |
| On-premise | Deployed in your own data center, connected to internal systems over the internal network |
| Air-gapped | No outbound connectivity at all, for environments where the perimeter is a legal boundary |
Customer data, transcripts, and documents are never used to train third-party models. Data retention is defined in the contract, and deletion follows the agreed schedule.
Before development begins, we agree on the metrics that will be used to assess the system: resolution rate without escalation, answer accuracy on the test set, response time, and cost per interaction.
Work is opened either as a project with a fixed scope, or as a retainer for ongoing development and operations. Scope, fees, and ownership of the deliverables (code and configuration belong to you) are set out in the proposal.
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