AIM Group · Ho Chi Minh City, Vietnam

Production-grade AI, engineered in Vietnam.

We design, build and operate AI systems for businesses — LLM applications and agentic AI, retrieval-augmented generation, computer vision, predictive machine learning and the MLOps that keeps them reliable in production. Delivered by dedicated engineering teams at Vietnam cost efficiency.

Discuss your project Explore services
  • LLM & Agentic AI
  • RAG
  • Computer Vision
  • Predictive ML
  • MLOps / LLMOps
  • Dedicated AI Teams
// how we deliver
  • PoC-first engagementValidate the use case on your data before committing to a full build.
  • Evaluation-drivenOffline evals, regression suites and production monitoring on every model and agent.
  • Deploy anywhereYour cloud (AWS, Azure, GCP), on-premise GPU or Vietnam-hosted infrastructure.
  • NDA & full IP transferYou own the code, models, prompts and data pipelines we build.

Who we are

An AI engineering partner, not a generalist software shop.

AIM Group is a Vietnam-based provider of AI solutions and software outsourcing. Our engineers specialise in the full lifecycle of applied AI: framing the problem, auditing the data, building and evaluating models, integrating them into your systems and operating them after launch.

We work with proprietary frontier models (Claude, GPT, Gemini) and open-weights models (Llama, Qwen, Mistral, DeepSeek) alike, and we choose the architecture that fits your accuracy, latency, cost and data-residency constraints — not the other way round.

Applied AI focusML, NLP, computer vision and generative AI as a dedicated practice.
Global deliveryServing clients in Vietnam, APAC and the United States with overlapping working hours.
Dedicated teamsNamed engineers who stay on your project, not a rotating pool.
Cost-optimisedSenior AI engineering at Vietnam rates, with transparent scope and pricing.

Services

What we build

End-to-end AI engineering services, each with concrete technical deliverables.

LLM Applications & Agentic AI

Assistants, copilots and autonomous agents built on frontier or open-weights models, grounded in your data and connected to your tools.

  • RAG pipelines: chunking, hybrid search (BM25 + vectors), reranking, citations
  • Multi-agent systems with tool use, function calling and MCP servers
  • Fine-tuning (LoRA / QLoRA), prompt optimisation, structured outputs
  • Guardrails, prompt-injection defences, human-in-the-loop checkpoints

Computer Vision

Vision systems for inspection, document processing and monitoring, from model training to edge deployment.

  • Object detection, segmentation and tracking (YOLO, DETR, SAM)
  • OCR and document AI: invoices, IDs, forms — including Vietnamese documents
  • Visual inspection and defect detection for manufacturing lines
  • Edge inference with ONNX Runtime, TensorRT, OpenVINO and NVIDIA Jetson

Machine Learning & Predictive Analytics

Classical and deep-learning models that turn historical data into forecasts, scores and recommendations.

  • Demand forecasting, churn prediction, credit and risk scoring
  • Anomaly detection and predictive maintenance on time-series and sensor data
  • Recommendation and personalisation engines
  • Feature stores, experiment tracking and model explainability (SHAP)

NLP & Speech (Vietnamese-first)

Language technology tuned for Vietnamese and multilingual use cases where generic models fall short.

  • Vietnamese NER, classification, sentiment and intent detection
  • ASR / TTS integration and call-centre conversation analytics
  • Multilingual chatbots and virtual assistants (web, Zalo, Messenger, voice)
  • Domain-specific embedding models and evaluation sets

MLOps & LLMOps

The engineering that takes models from notebook to production and keeps them accurate, fast and affordable.

  • CI/CD for models, model registry, feature and data pipelines
  • Serving with vLLM, NVIDIA Triton, KServe and TorchServe
  • Monitoring: data drift, latency, cost per token, tracing with Langfuse / LangSmith
  • Evaluation frameworks: offline evals, LLM-as-judge, regression suites

Data Engineering & Annotation

Reliable data foundations — because model quality is bounded by data quality.

  • Batch and streaming pipelines with Airflow, Spark, dbt and Kafka
  • Lakehouse and vector-store design (pgvector, Qdrant, Milvus, Weaviate)
  • Data labelling for CV and NLP with multi-pass QA workflows
  • Synthetic data generation and data-quality monitoring

AI Strategy & Consulting

Decide what to build, what to buy and what to skip before spending on engineering.

  • AI readiness assessment and use-case prioritisation by ROI and feasibility
  • Model selection: proprietary vs open-weights, hosted vs self-hosted
  • Architecture review, cost modelling and governance framework
  • Roadmap from pilot to enterprise rollout

Dedicated AI Teams

Extend your team with Vietnam-based AI specialists working in your process and tooling.

  • ML engineers, data scientists, AI backend engineers, MLOps engineers
  • Full squads with a technical lead, or individual staff augmentation
  • Your Jira, Git, Slack and sprint cadence; overlapping working hours
  • Scale up or down month to month

Not sure where to start?

Send us a one-paragraph description of the problem and the data you have. We will reply with a candid assessment of feasibility, approach and rough effort.

Get a free assessment

Solutions

AI applied to your industry

Typical use cases we implement, by business function and vertical.

Customer Service

  • RAG-powered support assistants on your knowledge base
  • Ticket classification, routing and auto-drafted replies
  • Call transcription, QA scoring and sentiment analytics

Operations

  • Document processing and data extraction (invoices, contracts)
  • Agentic workflow automation across ERP / CRM
  • Predictive maintenance from sensor and log data

Marketing & Sales

  • Customer segmentation and lifetime-value modelling
  • Campaign uplift and budget optimisation
  • Lead scoring and personalised content generation

Manufacturing

  • Camera-based defect detection and quality control
  • Production scheduling and yield optimisation
  • Safety and PPE monitoring on the shop floor

Finance & Banking

  • eKYC: ID OCR, face matching, liveness checks
  • Fraud and anomaly detection on transactions
  • Credit scoring with explainable models

Retail & E-commerce

  • Product recommendation and search relevance
  • Demand forecasting and inventory optimisation
  • Visual search and automated catalogue enrichment

Healthcare

  • Medical document and claims processing
  • Clinical-note summarisation and coding assistance
  • Patient triage and appointment assistants

Logistics

  • Route and load optimisation
  • ETA prediction and delay-risk scoring
  • Shipping-document OCR and customs data extraction

Process

How we take AI to production

A staged approach with a clear deliverable and a go / no-go decision at each step.

  1. 01

    Discovery & data audit

    Define the business objective and success metrics, inventory the available data, and assess quality, volume, labelling needs and compliance constraints.

    Deliverable: use-case brief, data-readiness report, risk register
  2. 02

    Solution design

    Choose the approach (rules, classical ML, fine-tuned model, RAG, agent), select models and infrastructure, and define the evaluation protocol before writing code.

    Deliverable: architecture document, model-selection rationale, eval plan, cost estimate
  3. 03

    Proof of concept

    Build a working prototype on a representative slice of your data and measure it against the agreed metrics — accuracy, latency, cost per request.

    Deliverable: runnable PoC, benchmark results, go / no-go recommendation
  4. 04

    Build & integrate

    Engineer the production system: data pipelines, model training or orchestration, APIs, integration with your existing applications and identity systems.

    Deliverable: production codebase, API contracts, infrastructure-as-code, test suites
  5. 05

    Evaluate & harden

    Run regression and adversarial evals, red-team prompts and agents, add guardrails and human-review gates, and load-test the serving stack.

    Deliverable: eval report, guardrail policies, security review, runbook
  6. 06

    Deploy, monitor & improve

    Release to your environment with monitoring for drift, quality, latency and cost. Retrain, re-prompt or re-index on a defined cadence based on production signals.

    Deliverable: monitored deployment, dashboards, SLA and improvement backlog

Technology

Our stack

Tools we use in production, grouped by layer. We are vendor-neutral and pick per project.

Foundation models

ClaudeGPTGeminiLlamaQwenMistralDeepSeekWhisperEmbedding models

ML & agent frameworks

PyTorchTensorFlowscikit-learnXGBoostLightGBMHugging FaceLangGraphLangChainLlamaIndexOpenCVUltralytics YOLO

Retrieval & data

pgvectorQdrantMilvusWeaviateElasticsearchOpenSearchPostgreSQLRedisKafkaAirflowSparkdbt

Serving & inference

vLLMNVIDIA TritonTensorRTONNX RuntimeOpenVINOKServeTorchServeFastAPIgRPC

MLOps & observability

MLflowKubeflowWeights & BiasesDVCLangfuseLangSmithPrometheusGrafanaOpenTelemetry

Cloud, infra & protocols

AWS SageMaker / BedrockAzure AI FoundryGoogle Vertex AIDockerKubernetesTerraformGitHub ActionsOn-prem GPUMCPA2AOpenAPI

Engagement

Ways to work with us

Pick the model that matches the maturity of your use case and the shape of your team.

Proof of concept

Fixed scope · fixed price

Validate one use case on your data with agreed success metrics.

  • Best for: first AI initiative, unproven feasibility
  • You get: prototype, benchmark report, production plan

Project delivery

Milestone-based

End-to-end build of a defined system with acceptance criteria per milestone.

  • Best for: clear requirements, defined integrations
  • You get: production system, documentation, handover, warranty period

Dedicated team

Monthly · scalable

A stable squad of AI engineers with a technical lead, embedded in your workflow.

  • Best for: continuous product development, multiple use cases
  • You get: named engineers, your tooling and process, monthly flexibility

Build-Operate-Transfer

Long-term

We build and run your AI team in Vietnam, then transfer it to you as your own entity.

  • Best for: establishing an in-house AI centre in Vietnam
  • You get: recruited team, office and operations, structured transfer

Trust

Security, data protection & AI governance

Controls we apply by default on every engagement.

Contracts & IP

  • NDA signed before discovery begins
  • Full ownership of code, models, prompts and datasets transferred to you
  • Clear licensing of any open-source and third-party components

Data handling

  • Data minimisation and PII redaction before data reaches any model
  • Encryption in transit and at rest; secrets managed, never hard-coded
  • Data residency options: your cloud tenant, on-premise or Vietnam-hosted

Access control

  • Least-privilege access, SSO and role-based permissions
  • Audit logging on data access, model calls and agent actions
  • Environment separation for development, staging and production

AI-specific safeguards

  • Input / output guardrails and prompt-injection defences
  • Human-in-the-loop approval for high-impact agent actions
  • Evaluation gates before every model or prompt release

Engineering practice

  • Version control for code, data and models; reproducible training
  • Model cards and decision logs for traceability
  • Automated tests, code review and infrastructure-as-code

Regulatory alignment

  • Vietnam Personal Data Protection Law (Law 91/2025/QH15, in force 2026)
  • Vietnam Law on Artificial Intelligence (risk-based framework, in force March 2026)
  • GDPR-aligned processing for EU and international clients

FAQ

Frequently asked questions

Not always. Many LLM and RAG use cases work with your existing documents and no labels. For computer vision and classical ML we start with whatever you have, assess coverage in the data audit, and can label, augment or synthesise data as part of the project. What matters most is that the data reflects real production conditions.

We benchmark both on your task before recommending. Hosted frontier models usually win on reasoning quality and time-to-market; self-hosted open-weights models win when you need strict data residency, predictable cost at high volume, or fine-tuning on proprietary data. Many production systems use a mix, routed by task.

A typical PoC runs four to eight weeks depending on data readiness and integration complexity. It ends with measured results against the metrics agreed at kick-off and a clear recommendation on whether and how to move to production.

Yes. We deploy into your AWS, Azure or GCP tenant using infrastructure-as-code, or on-premise GPU servers where data cannot leave your network. Self-hosted LLM serving with vLLM or Triton is a standard part of our stack.

With an evaluation set built from real cases, scored by a mix of deterministic checks, LLM-as-judge rubrics and human review. For RAG we track retrieval precision and recall, faithfulness and answer relevance; for agents we track task completion, tool-call correctness and safety violations. Every prompt or model change runs against the suite before release, and production traffic is traced and sampled for ongoing review.

You do. All deliverables — source code, trained weights, prompts, evaluation sets, pipelines and documentation — are transferred to you under the contract. We work in your repositories from day one where possible.

Vietnamese is a first-class language for us. We evaluate models specifically on Vietnamese text and speech, build Vietnamese evaluation sets, and fine-tune embedding or classification models where general-purpose models underperform on diacritics, regional dialects or domain vocabulary.

Our teams are based in Ho Chi Minh City (UTC+7). We keep overlapping hours with APAC clients by default and schedule daily overlap windows with US and European teams. Communication runs through your tools — Slack or Teams, Jira, GitHub — with written updates so nothing depends on a meeting.

Contact

Tell us about your project

Describe the problem and the data you have. An engineer — not a salesperson — will reply.

Head office

265 Ung Van Khiem Street, Binh Thanh District
Ho Chi Minh City 700000, Vietnam

Phone

+84 79 627 0089 (Vietnam)
+1 678 967 8666 (United States)

Hours

Monday – Friday, 08:30 – 18:00 (UTC+7)
Overlap windows arranged for US and EU clients

Prefer direct email? [email protected]