Our Engine

The Engineering Behind Intelligent Operations.

AI agents are only as effective as the systems behind them.

We combine problem-driven design, specialized intelligence, and structured execution to build AI systems that can reason, adapt, and remain accountable.

See what we build with it: Maritime AI Agents

01 · SOMR Engine®

Intelligence Beyond LLMs.

The right intelligence for the right problem.

Real-world decisions demand more than language understanding. Some problems require exploring scenarios, some identifying effective solutions under constraints, others learning from data or reasoning through complex information.

SOMR Engine® brings together four complementary capabilities for engineering intelligent decision systems.

  • Simulation

    Explore what could happen.

  • Optimization

    Find what works best under constraints.

  • Machine Learning

    Discover patterns from data.

  • Rule-Based Reasoning

    Apply explicit rules to support consistent, traceable decisions.

We don’t force problems into predefined models. We select the intelligence the problem actually needs.

02 · ChordX™

Intelligence, Composed.

From intelligence capabilities to problem-driven solutions.

SOMR Engine® provides the building blocks of intelligence. ChordX™ determines how those capabilities should be selected, combined, and organized to solve a specific problem.

Different problems may share underlying structures, but their objectives, constraints, and workflows are rarely identical. ChordX™ starts with the problem, not with a predefined AI model or algorithm.

Inspired by how a small set of musical chords can produce countless compositions, ChordX™ applies the principle of composition to intelligent decision systems.

The problem determines the composition. The composition determines the system architecture.

Define → Route → Design → Compose → Validate. From understanding human needs and identifying problem structures to designing workflows, selecting methods, and validating results.

ChordX™ is our overarching engineering framework, connecting problem understanding, intelligent composition, and structured execution.

Grounded in Business Knowledge. Before designing intelligent workflows, we identify the business concepts, relationships, and rules needed for the task. This lightweight knowledge foundation helps connect operational requirements to structured decisions and execution. See how it supports our agents

One Toolkit. Different Compositions.

Problem A · Scenario-Based Planning

Simulation+Optimization

Explore scenarios and identify feasible solutions.

Problem B · Evidence-Informed Decisions

Machine Learning+Rule-Based Reasoning

Identify patterns and support contextual judgments.

Illustrative capability combinations only; not mandatory sequences, and not claims about deployed products.

Engineering journey

  1. 01Define
  2. 02Route
  3. 03Design
  4. 04Compose
  5. 05Validate

Validation and human oversight are integrated throughout the engineering process.

03 · DEP

From Ambiguity to Execution.

Turning intelligent designs into structured, testable workflows.

ChordX™ determines how intelligence should be composed. DEP (Decision Execution Pipeline) translates that design into an explicit, executable workflow.

Real-world problems begin with incomplete information, competing objectives, and operational constraints. Problem and Interaction Tables (PT/IT) capture the human-facing requirements before they are translated into machine-execution logic.

DEP organizes the workflow into two types of nodes:

  • Decision Nodes (D). Evaluate alternatives and make structured decisions using defined decision methods.
  • Execution Nodes (E). Perform specific operations such as extracting information, transforming data, generating outputs, or executing authorized actions.

Each node has a defined purpose, inputs, outputs, method, and validation criteria. Together, they form a workflow that can be tested, inspected, and adapted to changing requirements.

Structured by design. Traceable by execution.

Evidence validation, error handling, and human oversight are incorporated where the decision risk requires them.

Layer 1 · Human-facing requirements

PT / IT

Problem definition · Interaction requirements · Expected outcomes

Layer 2 · DEP: machine execution

  1. E1· Extract
  2. D1· Decide
  3. E2· Execute

Illustrative node sequence — actual workflows are problem-dependent.

Engineering controls across the workflow

  • Contracts
  • Validation
  • Error handling
  • Human approval

Layer 3 · Verifiable outputs

Evidence · Decisions · Authorized actions · Traceability

04 · Our Engineering Approach

Beyond Vibe Coding. Into Software Engineering.

From research and method selection to software delivery, guided by reusable engineering playbooks.

Research & Method Selection

Define what needs to be measured, assess data feasibility, select suitable methods, and validate whether the evidence supports the decision.

Software Engineering & Delivery

Turn validated designs into modular, testable software through contract-first design and AI-assisted development.

Our Engineering Playbooks

  • Research Route
  • System Architecture
  • Implementation
  • Verification & Validation

The Engineering Advantage

  • Reusable

    Less reinvention across projects.

  • Reliable

    Testable, traceable results.

  • Faster Delivery

    Rapid prototype development.

~3 Daysto a Working Prototype

Demonstrated for selected moderately complex prototypes using AI-assisted engineering workflows.

Let's collaborate

Have a decision problem in mind?

From operational challenges to AI-powered decision systems, let's explore what we can build together.