Applied AI consulting
AI systems in production, with contractual ROI and operations that sustain themselves
We build AI infrastructure for companies that need to move beyond the experiment. From data architecture to the model in production, from governance to continuous monitoring. Every project closed by contract, with financial targets and validation deadlines agreed before the first sprint.
- Architecture, model and governance designed together. We deliver a complete system, not an isolated model.
- Pilot in production within 90 days with a contractually defined ROI target. Measurable result by quarter-end.
- Continuous operations with MLOps, monitoring and internal training. SLA agreed in writing.
Why the DIMX method works
We don't choose the model before understanding the architecture.
After operating AI across different sectors, the pattern is clear: success depends more on data architecture, pilot scope and governance than on model choice. Our method sequences those three decisions before any training. That's why we deliver in 90 days what others stretch across two years.
What we deliver by contract
Pilot in production with a defined ROI target, native integration with existing systems, real-time monitoring dashboard and continuous operating SLA.
What we don't sell
POCs with no path to production, ROI without data to back the projection, and contracts without a named owner for every agreed metric.
DIMX method
From architecture to model in production in a single quarter
Our method condenses into 90 days what traditional AI projects stretch across two years. Three sequential phases, each with a production deliverable and a financial indicator. No POC without a path forward, no promise without data, no clause without an owner.
Where we apply AI with proven returns
Operational volume beyond hiring capacity
We automate processes where the marginal cost of each new transaction exceeds the gain of hiring more people. AI frees up capacity where headcount stopped being the lever.
Historical data without query governance
We turn accumulated databases into actionable decisions. Churn, demand, fraud, risk. We architect RAG and predictive models over your proprietary data, with access governance and auditing built in from the start.
Skilled time consumed by repetitive tasks
We replace manual classification, extraction and generation with agents trained on the company's operational context. The team recovers hours for strategic work, with metrics compared against the prior baseline.
Customer service pressuring the structure
We deploy assistants trained on the company's real knowledge base, with contextual routing to humans where empathy matters. Response time drops an order of magnitude, satisfaction rises.
Process automation with agents
We replace manual classification, extraction and validation with systems that process at scale. Implementation integrated with your ERPs, CRMs and internal systems. Predictable, measurable returns from the first month of operation.
- Models trained on the company's real operational context
- Native integration with existing systems via API or events
- Productivity and quality metrics compared against pre-implementation baseline
Predictive intelligence over proprietary data
We turn history into anticipated decisions. RAG pipelines and predictive models over your private base, with versioning, access governance and auditing built into the architecture from day one.
- RAG pipelines with versioning and auditing of proprietary sources
- Predictive models integrated with executive dashboards and continuous experimentation
- Privacy and security governance designed with legal from the first day
Assisted customer service and support
We deploy agents trained on your knowledge base. First-level resolution in seconds, contextual escalation to humans where required. Customers wait less, the team spends hours on what genuinely requires judgment.
- Agents trained on real ticket volume and internal documentation
- Smart routing to humans preserving conversation context
- Real-time satisfaction, response time and resolution rate dashboard
AI embedded in digital products
We add an AI layer to your product: assisted generation, semantic search, contextual recommendation, orchestrated agents. Competitive differentiation with native integration to what already exists, without rewriting the foundation.
- Assisted journey design validated in production with real users
- Feature flags, usage metrics and agent orchestration embedded in the product
- Monetization strategy tied to the AI capabilities implemented
Method in three phases
Architecture, pilot and continuous operation in 90 days
Architecture and diagnosis
Fifteen days mapping data, processes and opportunities. Output: implementation plan with defined financial target, required resources and quarterly timeline.
- Technical audit of data, processes and integrations
- Feasibility, compliance and operational readiness analysis
- Executive plan with financial KPIs and production timeline
Pilot in production
Six to ten weeks implementing the prioritized use case. Trained model, integrations in production, ROI dashboard updated in real time. Payback target contractually agreed.
- Dedicated squad of product, data, engineering and design
- Native integration with existing systems, no replatform required
- Real-time ROI dashboard and weekly review with the board
Continuous operations and MLOps
We secure system continuity with monitoring, scheduled retraining and documented internal training. Operating SLA agreed in writing.
- MLOps with automated testing, monitoring and rollback
- Documented access, audit and responsible-use policies
- Training for product, operations and technology teams
Contact
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