Est. 2026 · Kuala Lumpur An Ai Teragrid Initiative

Where Agents are Engineered.

A boutique research laboratory designing production-grade AI agents with the patience of a workshop and the rigour of a foundry.

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Blueprint schematic of an engineered AI agent showing reasoning loop, tool surface, memory and token budget

Lab №01 Custom Fine-Tuning · Token-Efficient Architecture · Tera Grid Deployment agenticlab.com.my

Built with
  • Llama
  • ·
  • Qwen
  • ·
  • Mistral
  • ·
  • Gemma
  • ·
  • vLLM
  • ·
  • TGI
  • ·
  • Triton
  • ·
  • LoRA
  • ·
  • QLoRA
7–13wkMedian engagement
99.9%Production SLO
≤1.5kTokens / call median
APAC∞Primary region
II — The Process

Four steps. No shortcuts.

Each engagement moves through the same disciplined arc — from the first conversation to the moment your agent answers its first production request.

  1. 01

    Consultation

    We meet your team, study the workflow, and define what good looks like in measurable terms. No agent is built before the success criteria are written.

    • 1–2 weeks
    • Discovery interviews
    • Evaluation rubric
  2. 02

    Architecture

    We choose the base model, design the tool surface, and draft a token-efficient architecture. Where useful, we curate a fine-tuning corpus from your proprietary data.

    • 2–3 weeks
    • Model selection & fine-tuning plan
    • Cost & latency budget
  3. 03

    Sandbox

    The agent is assembled inside a private Lab Environment. We run adversarial evaluations against real cases until the rubric from Step 01 is satisfied.

    • 3–6 weeks
    • Adversarial & regression evals
    • Human-in-the-loop review
  4. 04

    Tera Grid Deployment

    The finished agent ships to Tera Grid — Ai Teragrid's production fabric — with autoscaling inference, observability, and per-request cost telemetry from the very first call.

    • 1–2 weeks
    • Autoscaling rollout
    • Observability & SLOs
III — The Principles

Three rules. The rest follows.

i

Measure first.

We refuse to build an agent without an evaluation rubric. If we can't tell when it works, we can't ship it.

ii

Tokens are money.

Every prompt is a budget. We design with retrieval, distillation and caching so production economics survive scale.

iii

Ship to the grid.

A demo is not a deployment. We hand off agents that scale, observe themselves, and report their own cost-per-request.

IV — The Sandbox

A Lab Environment for proprietary agents.

Every agent we build is staged inside a closed sandbox — a private rehearsal room where prompts, tools, and weights can be perturbed without consequence to your production systems.

V — Technical Detail

Custom fine-tuning. Token-efficient by design.

A

Custom model fine-tuning

We curate task-specific corpora from your proprietary data and fine-tune compact open-weights models — LoRA, QLoRA, or full-rank where the gradient justifies it — until the agent speaks your domain natively.

Methods
SFT · DPO · LoRA · QLoRA
Bases
Llama · Qwen · Mistral · Gemma
Eval
Held-out + adversarial suites
B

Token-efficient architecture

Long context is a luxury, not a strategy. We design retrieval over context-stuffing, distil large teachers into small students, and cache aggressively — so that an agent which costs a dollar in the demo costs a cent in production.

Patterns
RAG · Tool-use · Routing · Caching
Targets
≤ 1.5k tokens / call median
Telemetry
Per-request token & cost trace
C

Tera Grid deployment

Finished agents ship to Tera Grid — the production fabric operated by Ai Teragrid. Autoscaling inference, observability, and SLOs come standard. Your team gets a dashboard; we get the pager.

Runtime
vLLM · TGI · Triton
Region
APAC primary · global edge
SLO
99.9% availability
VI — Begin

Request a Lab Consultation.

Tell us where the agent should live in your workflow. A lab lead replies within one business day — never an autoresponder.

Or write directly to lab@agenticlab.com.my.

Appendix — FAQ

Frequently asked.

What is Agentic Lab?

A boutique R&D laboratory operated by AITG Sdn Bhd that engineers production-grade AI agents through custom fine-tuning, token-efficient architecture, and Tera Grid deployment.

Where is the lab based?

Headquartered in Kuala Lumpur, Malaysia. Engagements run remotely with on-site sessions across Southeast Asia and worldwide.

What does "token-efficient architecture" mean?

An agent design discipline that minimises the tokens consumed per task — compact prompts, retrieval over context-stuffing, distilled smaller models, aggressive caching — so production agents stay fast and economical at scale.

What is Tera Grid?

Tera Grid is the production fabric operated by Ai Teragrid where finished agents are deployed. It provides autoscaling inference, observability, and per-request cost telemetry.

How long does an engagement take?

From Consultation to Tera Grid Deployment, typical engagements run 7–13 weeks depending on data readiness and evaluation rigor.

Do you sign NDAs and DPAs?

Yes. We sign mutual NDAs before the first deep-dive and execute a Data Processing Agreement before any client data enters the sandbox.