Put AI to work.
With the right
technical partner.

Koeo helps businesses identify practical uses for AI, build and integrate the systems behind them, and keep them running. From a defined project to ongoing technical guidance, you work directly with us.

Engineering and technical leadership across enterprise software, cloud infrastructure and security.

Where we
can help.

Whether you have a project to deliver, an AI system to improve or technical decisions to work through, we help you move forward.

Build and integrate AI

Turn a useful idea into a working system. We build AI applications and workflows, connect them to your existing tools and information, and evaluate how well they perform.

Examples include technical knowledge assistants, account intelligence and internal workflow automation.

  • AI agents
  • RAG & knowledge retrieval
  • System integrations
  • Workflow orchestration
  • AI evaluation
  • Production deployment

Improve AI infrastructure

Make the systems behind your AI fit the workload. We help with inference platforms, cloud architecture and deployment, balancing performance, reliability and operating cost.

For teams building a platform, moving beyond a pilot or improving an existing deployment.

  • Inference optimization
  • Model serving
  • GPU & compute strategy
  • Cloud architecture
  • Scaling & reliability
  • Observability

Ongoing technical guidance

Bring experienced technical judgment into your team. Work directly with us on architecture, vendor choices, technical reviews and delivery priorities, with hands-on involvement where needed.

For leaders who need continuing support as their AI plans take shape.

  • AI roadmap
  • Architecture reviews
  • Vendor selection
  • Technical due diligence
  • Delivery oversight
  • Hands-on support

Access controls, data boundaries and operational ownership are considered from the start.

Selected work.

Systems built by us across enterprise AI, infrastructure and product development.

Grounded answers layer

From hours of waiting to answers in seconds.

Sourced technical answers in Slack for customer-facing teams. Internal work built on a large enterprise software company’s existing AI platform.

Typical response time, before → after
2–3 hours → 5–10 seconds
Over five months
About 600 users · 2,000 questions

Response time, not confirmed resolution. One knowledge base. Measurement details and user ratings are in the full study.

  • RAG & knowledge retrieval
  • System integrations
  • AI evaluation

Read the study

Illustration: a whiteboard with an ingestion pipeline sketched in marker.
Illustrative scene

GPU inference platform

From infrastructure setup to inference through a CLI.

An independent prototype, abstracting GPU infrastructure, model serving and routing behind a developer interface built around vLLM.

Developer CLI setup
A couple of minutes
Model loading, a separate step
Typically 2–3 minutes

Prototype timings vary with model size. One signed GPU partner MOU. Development concluded before production.

  • Model serving
  • GPU & compute strategy
  • Observability

Read the study

Illustration: graphics cards on a workbench with labeled cables, a power meter and a laptop.
Illustrative scene

Account intelligence workflow

Account preparation in hours. Context on demand.

An internal AI workspace built to connect account information and actions across existing tools, with human review and established access permissions.

Observed account preparation
2–3 days → under two hours
Account report generation
Under ten minutes

Observed experience, not a formal time study. Report generation and completed preparation are separate measures.

  • System integrations
  • Customer signals
  • Account context

Read the study

Illustration: a laptop with an abstract account overview, charts and a notebook.
Illustrative scene

Also built

  • Surforme

    A consumer health web app built end to end in approximately 3–4 months, with source-linked Portraits and automated quality checks before delivery. About 100 activated accounts in a live beta at surforme.com.

    Read the study

Illustrations depict the settings, not actual systems or customer screenshots. Each study explains the context and results.

How it
works.

Start with the challenge. We’ll help define the next step and agree on a way of working that fits your team—from a focused project to ongoing technical support.

Discuss your challenge
Discuss your challengeShare the problem, context and desired outcome.

Tell us what you want to improve, where things stand and who is involved. You can bring a defined project, an existing system or a technical decision you need help working through.

What we clarify together
The problem
What needs to work better?
The context
Your people, systems and constraints
The outcome
What would a useful result look like?

A clear starting point

Agree on the scopeDefine priorities, responsibilities, fees and success measures.

Together, we define the priorities, what success looks like and the right engagement: a focused assessment, a defined project or ongoing support. Scope, responsibilities and fees are agreed before work begins.

Your engagement brief
Scope
Priorities and deliverables
Success
How we’ll evaluate the work
Ownership
Who does what
Fees
Cost and engagement structure

Agreed before work begins

Work alongside your teamBuild, improve or advise, with regular reviews.

We build, integrate, improve or advise according to the scope. Progress is reviewed with your team, with working systems, findings and recommendations you can evaluate along the way.

A shared delivery cycle
  1. DeliverA working increment or recommendation
  2. Review togetherEvaluate it against the agreed goals
  3. RefineUse the feedback to guide the next iteration

Back to delivery, with a clearer next step

Put the work into practiceSupport adoption, transfer knowledge and review ongoing priorities.

We help your team use and maintain what’s delivered, with documentation and knowledge transfer suited to the engagement. Ongoing work follows an agreed cadence, with priorities reviewed as your needs evolve.

Support that fits the engagement

Handover

  • Documentation
  • Knowledge transfer
  • Clear ownership

Ongoing support

  • Agreed cadence
  • Technical guidance
  • Evolving priorities

Your team knows what comes next

Technical depth.
Business perspective.

Francois Neron, smiling, in front of a painting.

Francois Neron

Founder & technical lead

The experience behind Koeo spans enterprise software, cloud infrastructure and security, from hands-on engineering and architecture to CIO and CEO roles. Since 2014, that work has included enterprise deployments, customer integrations and building products from the ground up.

You work directly with us on technical decisions and delivery. We bring in specialists where the scope calls for them, with clear responsibilities throughout the engagement.

Enterprise deployments and security programs across Falcon Cloud Security, ASPM and AIDR.
Terraform, Vault and Consul across Fortune 500 accounts: cloud adoption, secrets, platform standardization.
Merchant integrations with more than US$10B of order volume behind them; SDK demos that cut integration time in half.
CIO across cloud, IoT and data pipelines.
CEO of a consumer health web application, currently in beta with source-linked Portraits and automated quality checks.
Banking software, where a full-stack career started in 2014. Ten-plus products shipped for Montreal startups since.

Built around
your priorities.

The right technical choice depends on what your business needs to achieve. We weigh usefulness, cost and reliability together, whether we’re building a system, improving infrastructure or helping your team decide what comes next.

Discuss your
challenge.

Tell us what you want to build, improve or work through, and where things stand. We’ll review your inquiry and get back to you to discuss fit and next steps.

Discuss your challenge

Need help choosing a direction? Our optional US$350 assessment includes a focused session and a written recommendation. See assessment details.