AI, data, and cloud systems built for production.
We build dependable AI systems, reliable data platforms, and secure cloud foundations for organizations where security, regulation, and operational complexity matter.
Deepest in health and life sciences. AWS-first and portable by design.
What we help clients accomplish.
Three service areas, one standard: systems built for real operations. We provide the engineering and architecture needed to deliver them.
AI Systems & Automation
We build AI systems for document intelligence, knowledge retrieval, decision support, and workflow automation. Measurable evaluations, human oversight, security controls, and production monitoring are included from the start.
Make fragmented data usable
We build governed data platforms that resolve identities, preserve lineage, and turn complex claims, clinical, pharmacy, commercial, and vendor data into reliable analytical and operational models.
Build secure cloud foundations
We build secure AWS foundations with infrastructure-as-code, identity and encryption controls, CI/CD, observability, environment separation, and cost management aligned to your operating environment. We use containers, open formats, and client-owned code when portability justifies the added cost.
What you can expect.
Commitments agreed before work begins, with a shared definition of done.
Clear scope
We document the problem, constraints, success measures, responsibilities, and decision points before work begins.
Controlled delivery
We test high-risk assumptions early against agreed measures, including security, human review, and operational requirements.
Client ownership
Code, infrastructure, documentation, and decision records are delivered to client-controlled environments where practical. Ownership and support are agreed upfront.
AI and data engineering for health and life sciences.
We build the pipelines, models, platforms, and controls that turn complex industry data into reliable products and workflows.
We engineer cloud pipelines and governed models for medical and pharmacy claims, eligibility, remittance, payer, plan, NPI, provider, and facility data. Entity resolution, validation, anomaly detection, and machine learning reconcile sources and support claims analytics and workflow automation.
We build HL7 v2, FHIR, API, and document pipelines for EHR data. Clinical NLP and document intelligence structure notes, extract relevant information, and normalize terminology, with provenance, measurable evaluation, security controls, and human review.
We create governed data layers across claims, formulary, coverage, transaction, hub, specialty-pharmacy, and contract data. Identity resolution, document extraction, taxonomy alignment, lineage, and change detection support access-barrier identification, formulary-change tracking, launch planning, field workflows, and patient services.
From problem to solution.
Four steps with agreed deliverables, decision points, responsibilities, acceptance criteria, and handoff expectations.
Frame
Define the workflow, users, data, risks, constraints, and the measurable business result.
Prove
Test the approach against representative data with explicit evaluation criteria.
Ship
Deliver the application, pipelines, infrastructure, documentation, and controls into your environment.
Operate
Monitor quality, cost, adoption, and exceptions, then expand only what produces measurable value.
Why work with ClavesIQ.
A focused, accountable delivery model led by experienced practitioners.
- W.01Experienced practitioners design and deliver the work.The team you meet remains accountable for architecture, delivery quality, and outcomes.
- W.02AI is part of an observable production system.Evaluation, human review, monitoring, and rollback are built in.
- W.03Domain constraints shape the design.Claims, clinical, pharmacy, commercial data, security, and regulatory requirements are addressed from the start.
- W.04Engagements are tied to measurable outcomes.Each project begins with an agreed operational or business metric.
Architecture and delivery stay connected through handoff.
Assumptions, tradeoffs, risks, and costs are surfaced early.
Success criteria are agreed before implementation.
Security, privacy, traceability, and human oversight are design requirements.
How we deliver.
Technical leadership brings 15 years of experience across AI, data, engineering, and the US health and life sciences ecosystem. Delivery practitioners average 10–12 years in their respective fields. Named personnel and relevant experience are provided during proposals and procurement.
- D.01Experienced practitioners stay involved throughout.The same practitioners remain involved from architecture through production readiness.
- D.02Teams are matched to the problem.Composition reflects the skills, responsibilities, and workload the engagement requires.
- D.03Specialist partners are disclosed when used.Their responsibilities and governance are documented before engagement.
- D.04You own the result.See Client ownership above for what that includes.
- D.05Responsibilities are named before work begins.Delivery milestones and acceptance criteria are agreed up front.
The AI Opportunity Assessment.
Two weeks. One clear decision. We assess the workflow, data, technical options, controls, and business case, then deliver an evidence-backed recommendation and practical path forward. The right answer may be to build, buy, partner, defer, or stop.
What procurement can expect.
The basics, stated plainly. Contract-specific terms are finalized before work begins.
- ·ClavesIQFounder-led, operating since 2025.
- ·Incorporated federally in CanadaBased in Toronto, Ontario.
- ·99 Broadway Ave, Toronto, ONRegistered business address.
Start with what you're trying to unlock.
Tell us about the workflow, data, delivery risk, or decision in front of you. We'll respond within one business day. If ClavesIQ is not the right fit, we'll say so.