# Capabilities for the intelligent enterprise.

> Boltcliq solutions: applied AI, AI native companies, physical AI, digital twins, data and cloud, platforms, ontologies, business intelligence, AI education, AI factories and neo cloud.

Canonical URL: https://www.boltcliq.com/solutions
Part of: https://www.boltcliq.com/llms.txt

From data foundations to AI factories, we deliver the full ladder from raw data to autonomous operations.
- Software is now a commodity. Intelligence is not. We build the rungs between your raw data and an organization that runs itself with oversight.
### What solutions means here
- Our solutions are services and delivery, not software licences. We are a full-stack AI company. Forward deployed engineers embed with startups and enterprises, build on their real systems from the first week, and hand over capability, not just code.
- Each solution below is a place to start. Some organizations need data foundations before anything else. Others already have clean data and need an ontology, or agents, or compute. We meet you at the rung you are on and build upward from there.
- Every solution can run on the Boltcliq products or on your own stack. The platform is there when it helps. It is never a condition of working with us.
### Eleven solutions
**Sovereign AI**
- Own your AI. We build custom and fine-tuned models on your own data and deploy them where you decide: on your premises, in your private cloud, on Boltcliq cloud or with a local provider. You keep the model, the data, the keys and the control.
**Applied AI**
- AI that runs inside real operations, on real data, with accountable humans in the loop. We move models out of the notebook and into the workflows where decisions are made. We stay until the result is measured and owned by your team.
**AI Native Companies**
- We build and back companies designed around intelligence from the first line of code. Our engineers act as founding partners on architecture, platform and first product. We also help set up the operating model that lets a small team run like a large one.
**Physical AI**
- Intelligence that sees, decides and acts in the physical world. Farms, factories, mines, ports and grids produce the signals that matter. We design edge-to-cloud pipelines that keep working when connectivity does not.
**AI Digital Twin**
- A living model of your operation that you can query, simulate and optimize. Twins are built on your ontology and fed by operational data. Leaders can ask what is happening, what happens next and what to do about it.
**Data & Cloud**
- The foundations every intelligent system stands on. We integrate, clean and govern scattered data, then run it on cloud infrastructure that is secure and cost-aware. We also modernize legacy estates.
**Platforms**
- Operating platforms that bring data, models and teams into one place. We replace dozens of disconnected tools with one surface that analysts, operators and agents share. The result is production-grade platform engineering you can own.
**Ontologies**
- The shared model of your business that lets humans and agents reason about it. We define objects, relationships, rules and actions once, and use them everywhere. It is the center of everything we build.
**Business Intelligence**
- Analysis at the scale of the whole organization, in the hands of people who decide. A governed semantic layer means every team counts the same way. Plain-language questions return answers you can trace to source.
**General AI Education**
- Building the people who will build, run and govern intelligent systems. Programs run from executive briefings to hands-on engineering academies. They are practical, local and tied to real systems.
**AI Factories**
- Repeatable production lines for building, testing and shipping intelligence. We design the compute, data, tooling and process that turn ideas into deployed models and agents. We also help set up the team that operates it.
**AI Software Factory**
- A governed line where AI agents build, test and ship software while your engineers set intent and approve. We design the specifications, context, sandboxes, gates and metrics that make agent-written code safe to release.
**Neo Cloud & Inference**
- Sovereign compute and inference, delivered with local partners. We design the architecture, integrate regional infrastructure players and operate the software layer. The goal is low-latency, compliant AI with local control.
### The intelligence ladder
**Data**
- Connect databases, spreadsheets, documents and partner feeds. Make the data trustworthy: clean, governed and traceable to source.
- Solutions: Data & Cloud
**Integration**
- Join systems so that a customer in billing is the same customer in support. Reliable pipelines replace weekly exports and manual copying.
- Solutions: Platforms
**Ontology**
- Model the business as objects, relationships, rules and actions. This is where raw records gain meaning that people and machines share.
- Solutions: Ontologies
**Analytics**
- Ask questions of the whole organization and trust the answers. A semantic layer makes every report use the same definitions.
- Solutions: Business Intelligence
**Agents**
- Let software take steps, not just report. Agents propose and perform actions on the ontology with permissions, approvals and a record.
- Solutions: Applied AI
**Autonomous operations**
- Routine work runs itself, with oversight. People handle exceptions, set policy and decide what the organization should do next.
- Solutions: Physical AI, Digital Twin
### Why the order matters
- Most failed AI projects skip rungs. A team builds an agent before its data is joined up, so the agent guesses. Or it builds dashboards before anyone agrees what a “customer” is, so every number is argued about. The ladder is a sequence because each step depends on the one beneath it.
- Skipping is not always wrong. A well-scoped pilot can run on a thin version of each rung. But thin must be honest. We tell you which rung is carrying weight and which is a placeholder, so you can invest where it counts.
- You do not have to climb alone or all at once. Many organizations begin at the rung that hurts most and widen from there.
### Forward deployed engineers
- A forward deployed engineer is a software engineer who works inside your organization. They join your meetings, read your data and learn how the work really happens. They build on your systems from the first week and ship early.
- This model suits problems that do not fit a product demo. A bank with three core systems, a clinic network with paper records, a co-operative with a spreadsheet for a registry. The answer depends on details, and details are found on site.
- We hand over as we go. Your people learn the architecture, own the ontology and run the system. We leave capability behind.
- Embedded on site and online
- Real systems from week one
- Handover is part of the plan
### Ways to start
**One use case**
- Choose a single decision, workflow or report that matters. We build it end to end on your data so you see value early and learn what the next step is. Scope and pricing are agreed per engagement.
**A data foundation**
- If your data is scattered, start there. We integrate the sources that matter, put governance in place and give you one place to build from. This is the base for analytics and agents.
**An ontology**
- If your data is in decent shape but means different things to different teams, model the business. We work with process owners to define objects, links, rules and actions you can reuse.
### Solutions and products
- The solutions are how we work. The products are what we build to make that work repeatable. Zeus carries the ontology, Odin the identity, Monolith the agent governance, Argus the runtime and Cyclopes the record.
- On any engagement we use them where they fit and your own tools where they do not.
- Ontologies and Business Intelligence lean on Zeus
- Applied AI and AI Factories lean on Monolith and Argus
- Every solution reports to Cyclopes if you want it to
### Questions
- Do I need to use Boltcliq products to work with you?
- No. Solutions can run on our products or on your own stack. We recommend the platform where it fits and tell you honestly where it does not yet.
- How big is the team that joins us?
- It depends on the scope. Many engagements start with a small group of engineers and an architect working with your team, and grow only if the work calls for it.
- Who owns the result?
- You do. The ontology, the data pipelines, the documentation and the skills are handed to your team. That is the point of the handover step.
- How do you price engagements?
- Scoped per engagement, around an outcome you can verify. We do not publish rates.
- Can you work with our data residency rules?
- Yes, and we design for them from the start. Architecture options include your own cloud account, a local data center and on-premises, depending on what the rules require.