AI services · generative, agentic, computer vision, ML

Artificial Intelligence & Machine Learning Services

Production AI on your own data, with an engineer accountable for every model that ships.

Dedicatted designs, builds and runs AI systems for enterprises: generative and agentic applications, computer vision and predictive models, on AWS and in your own accounts. Every model ships with its evaluation set written first and passes the same review and sign-off as any other change.

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AWS GenAI + Agentic AI The only GenAI and MSP partner in Canada, with the Agentic AI specialization.

What are AI services?

  • What are AI services?

    AI services cover the design, development and operation of artificial intelligence systems: generative AI applications, AI agents, computer vision and machine learning models, built on a company’s own data and run in production.

  • What do AI services include?

    They include use-case discovery, data readiness, model selection and fine-tuning, retrieval and agent architectures, evaluation, deployment on cloud infrastructure, and monitoring and retraining once live.

  • What does an AI services company do?

    An AI services company turns a business problem into a working AI system: it finds where AI pays off, builds and evaluates the model or agent, integrates it with existing systems and keeps it accurate and secure in production.

Our core AI services

  • Generative AI

    Move from a first proof of concept to custom LLMs you own, on Amazon Bedrock or OpenAI, with your data and IP under your control.

    RAGBedrock and OpenAI integrationLLM fine-tuningDomain chatbotsContent generation

    Build with generative AI

  • Agentic AI

    Put multi-agent systems to work across a whole workflow: planning, reasoning and acting under guardrails for security and compliance.

    Multi-agent orchestrationWorkflow automationDocument processingAI copilots

    Put AI agents to work

  • Computer Vision

    Turn cameras into instruments: quality inspection, object detection, document processing and video analytics, built on your footage and run in your cloud or on the edge.

    Quality inspectionObject detectionDocument processingVideo analyticsEdge deployment

    See computer vision services

  • ML & Predictive Analytics

    Forecast demand, failures and churn from your own data, with the MLOps platform that deploys, monitors and retrains the models.

    Demand forecastingPredictive maintenanceAnomaly detectionCustomer churnMLOps

Need something not listed? Ask an AI consultant. One business day to a first read.

Where engagements start

Three ways to start. Each has a fixed scope and ends in something your team keeps.

  • AI readiness assessment

    4 weeks · AWS-funded

    Your AI use cases ranked, your data checked, a roadmap to production.

    • Opportunity map
    • Data readiness report
    • Roadmap and first build scoped
    See the assessment
  • Generative AI pilot

    Scoped in the first call

    A working assistant on your documents, in your AWS account, measured first.

    • Evaluation set before the model
    • Runs in your account
    • A path to production
    Book a pilot call
  • Agentic workflow

    One process · scoped in the first call

    An agent for one high-volume process, with guardrails and human sign-off.

    • Process mapped and instrumented
    • Guardrails and approvals built in
    • Hours saved, reported
    Book a workflow call

How are AI services delivered?

  • How do companies use AI services?

    Companies use AI services to automate document-heavy processes, add assistants and agents to their products and operations, inspect and detect with computer vision, and forecast demand, churn and failures from their own data.

  • What is the AI services process?

    The process runs assess, pilot, production, operate: opportunities ranked and data checked, a pilot with its evaluation set written first, deployment in the client’s cloud account under review and sign-off, then monitoring and retraining.

  • How long do AI projects take?

    The assessment takes four weeks. A pilot is scoped in the first call against the process you bring, in weeks rather than months; production rollout depends on integrations and data and is scoped after the pilot.

How an engagement runs

Engineers use AI at every stage. A person owns every result that ships.

  1. Assess

    Opportunities and data

    • Use cases ranked by value and effort
    • Data and integration readiness checked
    • The first build scoped and priced
  2. Pilot

    Evaluation set first, then the model

    • Success criteria and test set written up front
    • Model, retrieval or agent built against them
    • Results reported against the numbers
  3. Production

    Shipped under your controls

    • Review and sign-off like any other change
    • Deployed in your cloud account
    • Security and compliance built in
  4. Operate

    Kept accurate and affordable

    • Monitoring for drift and cost
    • Retraining and prompt updates on a schedule
    • Managed operations on published tiers

What are the benefits of AI services?

  • Why use AI services?

    AI services put working models into production faster than an in-house team can hire for, with the evaluation, security and operations discipline that keeps them accurate and compliant.

  • What are the key benefits of AI services?

    Hours returned from manual work, faster decisions from your own data, new product capabilities such as assistants and agents, and a lower cost per task where AI replaces repeated human effort.

  • How do AI services improve business performance?

    By automating high-volume processes, surfacing forecasts and anomalies early, and giving staff and customers assistants grounded in company knowledge, measured against a baseline taken before the work starts.

The stack behind the practice

  • Bedrock Amazon Bedrock
  • sagemaker SageMaker
  • hugging face Hugging Face
  • pytorch PyTorch
  • databricks Databricks
  • amazon s3 Amazon S3
  • postgresql PostgreSQL
  • aws glue AWS Glue
  • opencv OpenCV
  • roboflow Roboflow
  • detectron2 Detectron2
  • onnx runtime ONNX Runtime
  • mlflow MLflow
  • kubernetes Kubernetes
  • gitlab GitLab
  • datadog Datadog

Featured technology partners

The Only GenAI & MSP Partner in Canada

As the only AWS GenAI and MSP partner in Canada, we empower businesses to build scalable cloud solutions that drive innovation.

Read More

Bring us one process. We will tell you in a day whether AI pays for itself there.

Tell us the process or the data. An AI consultant replies within one business day with relevant experience and a first read.

Book a free meeting

Insights

FAQ

How do you keep our data out of public models?

Models run in your AWS account or ours under contract; nothing you share is used to train a public model. Retrieval systems read your documents at query time rather than baking them into weights, and access follows your existing permissions.

Do you build on AWS only?

AWS is our primary platform and where our competencies are held. We also deliver on Azure and Google Cloud, and integrate OpenAI models where they fit.

Who owns the model and the code?

You do. Code, prompts, evaluation sets, fine-tuned weights and the infrastructure definitions are delivered into your repositories and accounts.

How do you measure whether it worked?

Every engagement starts with a baseline and an evaluation set written before the model. Results are reported against them, and the same numbers are monitored once the system is live.

What does a pilot cost and how long does it take?

The assessment is fixed-scope over four weeks and AWS-funded. Pilots are scoped in the first call against the process you bring; you get a written scope and price before any work starts.

Can we start with one process?

Yes. Most engagements start with one high-volume process or one assistant, measured end to end. The next use case joins under the same team once the first is in production.

How do you use AI in delivery?

Our engineers use AI at every stage: reading data and systems, drafting code, tests and documentation. Every result is verified by an engineer against your standards before it ships.

Question not answered? Ask an AI consultant. Same-day reply on feasibility questions.

What are AI services?

AI services help enterprises put artificial intelligence into production: generative AI solutions built on your own data, agentic AI that automates workflows and decision making, computer vision, and machine learning models with the MLOps platform to run them. Dedicatted delivers AI services and consulting on AWS for enterprise clients in healthcare, logistics, retail, manufacturing and finance, from use case to production.

Enterprise AI services and consulting

Dedicatted is an AI services company and AWS partner with the Generative AI and Agentic AI competencies. Our AI engineers design, build and operate generative AI applications, multi-agent systems, computer vision solutions and predictive models that improve operational efficiency, customer experience and real-time decision making. Every model ships with its evaluation set written first, runs in your AWS account under your security controls, and is monitored and retrained once live.

Our AI services include:

  • generative AI consulting and development on Amazon Bedrock and OpenAI
  • agentic AI and workflow automation, including intelligent document processing
  • computer vision for quality inspection, detection and video analytics
  • machine learning, predictive analytics and MLOps platforms
  • AI opportunity and readiness assessments
  • AI-augmented software development

Get started with an AI consultant

Tell us the process or the data. Our team responds within one business day with relevant experience and a proposed first step.


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