Outcomes First
Every engagement starts with the business problem. Recommendations follow the evidence, and every engagement is anchored to defined, measurable outcomes before a line of code is written.
Most AI projects never reach production. Ours do — 15× more often.
We help you find the workflows where AI will actually pay off, then take them from pilot to production through a systematic process that starts with your business problem, ends with working AI in your existing stack, and delivers measurable ROI you can point to.
A delivery rate 15× the global benchmark
Across the industry, 5% of AI projects reach production. Across ours, 75% do. We get there by leading with the business outcome, designing for the people who actually use the system, and engineering for the security and auditability that regulated industries require — from day one, not as an afterthought.
A proven path from your highest-value workflow to AI in production
Every engagement starts with understanding your business. From there, a clear sequence takes you from identifying where AI will move the needle, to a working pilot, to scaled capability you own. You enter at the stage that matches your AI maturity.
Is this you?
Pick the statement that sounds most like you, or take our 5-minute AI maturity survey for a more detailed look at your readiness. We confirm the fit in a free discovery call.
Pre-engagement Diagnostic
Before committing to a lane, we run a focused diagnostic to understand your AI maturity
across strategy, data foundations, and use case readiness. You walk away knowing the right entry point
before spending a dollar.
AI Discovery Workshop
A 1-2 day working session with your key leads to surface your highest-confidence AI opportunities. You walk away with a prioritized map of 2-4 use cases, each framed as a concrete business problem with an initial value case, specific enough to secure sponsorship or move directly into a build.
AI Strategy Sprint
For organizations that need a structured, evidence-based strategy before committing budget to a specific build. Over 2-4 weeks we go deep across your business functions, data architecture, and technology landscape, with one to two of your staff working alongside us, and deliver a roadmap that sequences your full AI opportunity by impact, feasibility, and data readiness.
Foundations Sprint
A 2-4 week cross-functional sprint covering data, architecture, and organizational context, building
the pipelines and foundations your future AI will actually run on. The right starting point when
infrastructure gaps would otherwise block a build.
Use Case Pilot
For organizations with a specific AI opportunity and ready to build. We start by establishing the
data foundation for the use case, then move through prototype development with defined goals, built in
your actual environment with the right guardrails for regulated industries. You walk away with a working
prototype, a production path, and the data infrastructure to accelerate the next use case.
Center of Excellence
We stand up your internal AI team from first deployment to fully autonomous delivery,
with our experts embedded and transferring knowledge throughout. You own the capability, not just the
output.
Capabilities
Pre-built accelerators that compress the time from problem to production.
PlantOps
Challenge: Batch manufacturers run on scattered operational data across MES, SCADA, ERP, and historians, with no unified view of why some batches succeed and others don’t.
Solution: A vendor-agnostic industrial AI platform that sits on top of existing systems, unifying production data and applying AI for quality control, Golden Batch monitoring, anomaly detection, and predictive maintenance, without replacing what’s already there.
Impact:
- 10-20% scrap and defect reduction
- 5-12% reduction in process variability
- 3-7% yield improvement
- Typical payback period 3-9 months
Scout
Challenge: Marketing and content teams spend the majority of their time on page assembly rather than message refinement, with AI tools that generate content divorced from the actual design system and block structure.
Solution: A WordPress AI plugin, built by Carimus’s AI engineering team, that reads block definitions directly from the theme’s live block registry and converts natural-language prompts into fully structured, on-brand page drafts, using only components that actually exist in the theme.
Impact:• Significant reduction in time from page brief to publishable draft• Higher brand consistency across content output• Content teams freed to focus on message quality rather than page construction
AI Media Planner
Challenge: AdOps and media planning teams spend hours creating media plans manually, with no systematic way to distribute across channels or optimize audience targeting from historical data.
Solution: An AI-native media planning platform that transforms marketing briefs into ready-to-use media plans, distributes them across channels from Google Ads to DOOH, and generates audience recommendations from historical campaign data, integrated with your existing systems and ad infrastructure.
Impact:
- 30-60% reduction in media planning time
- 2-3x more campaigns created with the same team
- 3-5x increase in reach efficiency and ROI
- 10-15% productivity improvement across AdOps
Client Cases
From concept to production, across industries and use cases.
NVIDIA / Holoscan
Challenge: Medical AI applications require real-time, regulatory-compliant video processing at clinical edge, where standard cloud-dependent infrastructure can’t meet latency, reliability, or compliance requirements.
Solution: A deployment leveraging NVIDIA Holoscan for real-time AI inference in medical imaging and edge clinical environments, with regulatory compliance built in from the start and fully local processing.
Impact:
- Instant image segmentation and classification
- Heatmap visualizations for clinical review
- Fully local processing on a Linux-based device, without cloud dependency
Compensa xGenie
Challenge: Organizations lose significant time and introduce errors when employees manually transfer data between documents, systems, and formats, particularly in procurement, compliance, and contract-heavy workflows.
Solution: We developed an AI-based data extraction tool that automates document processing without requiring templates, pulling structured data from unstructured sources accurately and at scale, deployed on your existing infrastructure.
Impact:
- Process documents in minutes vs. hours
- Greater accuracy and consistency across outputs
- Stronger compliance with automated checks
Hologic / Holli
Challenge: Sales reps and field teams needed instant access to Hologic-specific product, competitive, and clinical information during live customer interactions, without relying on external LLMs or exposing proprietary data.
Solution: An AI knowledge base that crawls Hologic’s own URLs and lets users ask product-specific questions, receiving pointed answers with source links, privately made and not serving data to external models.
Impact:
- Custom AI-powered search across competitive, clinical, and resource content
- Analytics on usage and effectiveness built in
- Extendable into the sales playbook as a rep tool
Enterprise-grade AI infrastructure, built in from day one
In regulated sectors, compliance and security are design inputs, not late-stage reviews. We build with auditability and explainability as structural requirements — and where data sensitivity demands it, we run models inside your own infrastructure so sensitive data never leaves your environment.
Health & Life Science
- IPAA-governed clinical data, FDA/EMA workflows, and explainability for Class I device environments (EU MDR). ISO 13485 certified, with production experience across IEC 62304, HL7/FHIR, and medical device cybersecurity.
Energy & Utilities
- Reliability and safety standards for critical infrastructure, with hybrid and on-premise deployment where data transfer is restricted.
Manufacturing
- Industry 4.0 quality standards, computer vision and predictive maintenance with strong data-access controls and traceability.
Public Sector
- Deep experience under EU GDPR, the EU AI Act, and equivalent frameworks governing citizen data in AI systems.