Services

Symbiotic Dynamics brings futuristic technological ideas to life. We provide research-grade AI, machine learning and robotics services, spanning independent capability prototyping, technical direction setting, and preparation of high-stakes technology demonstrations.

Our work focuses on intelligent systems in interaction with the human: large-scale language models, robotics, multi-agent and embodied AI, as well as graph-based systems and innovative, AI-first governance.

Explore & Build

Engineering of new capabilities, research, experimentation, and early-stage prototyping.

Lead

Establishment of tailored technical direction and setting up effective innovation teams.

Demonstrate

Preparation of convincing demonstrations of innovative capabilities for internal and external audiences.

Govern

Governance and assurance layers for autonomous and agentic systems, anchored in Policy Cards.

Service areas

We push innovation up the TRL-scale, from early idea to effective demonstration and compliant capability in production.

Stage: Explore & Build

Independent AI Research & Prototyping

Independent exploration and prototyping of advanced AI, ML, language, graph and embodied systems.

  • Research sprints
  • Concept prototypes
  • Innovating upon existing capability
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Stage: Lead

Technical Direction & CTO Support

Setting of technical direction for innovation, architecture and team structures for AI-intensive initiatives.

  • Technology and architecture assessment
  • Team alignment & role structure
  • Roadmaps
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Stage: Demonstrate

Demo Excellence & High-Stakes Readiness

Stabilisation and refinement of critical technology demonstrations for high-stakes presentations.

  • Demo audit & refactoring
  • Runbooks, fallbacks & narrative preparation
  • Team roles & responsibilities
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Stage: Govern

Policy Cards & AI Governance

Governance, control and audit layers for autonomous and agentic systems using Policy Cards.

  • AI-first Runtime governance
  • Machine-readable controls
  • Pilot programmes
View Policy Cards

Independent AI Research & Prototyping

Symbiotic Dynamics conducts research and prototyping for intelligent systems. Work spans from traditional ML, language models, knowledge graphs, to embodied systems, robotics, autonomous systems, and related technologies.

Our emphasis is on future capability development and not only the development of individual models in isolation. We harness latest technological developments to create new value adding capabilities in relevant domains. This includes identifying feasibility, architectural possibilities, testing assumptions and building prototypes. The aim is to establish what is technically feasible and beneficial before larger commitments are made. How can we achieve new useful capability in the simplest way possible?

Scope of work

  • Formation of new capability through focused technical exploration
  • Early-stage research
  • Prototyping and experimental evaluation
  • Architecture exploration and capability mapping
  • Assessment of integration requirements
  • Validation of technical feasibility

Domains

  • Data extraction and natural language processing
  • Large language models, retrieval-augmented systems
  • Knowledge graphs, ontologies, relationship extraction
  • Graph machine learning and relational reasoning
  • Agentic AI, multi-agent systems and orchestration
  • Embodied AI, robotics and simulation environments
  • AI Governance at runtime

Engagement patterns

  • Research sprints with defined questions and technical options
  • Prototype development to test feasibility of a new idea
  • Experimental workflows, e.g., experimental environments for embodied or digital agents
  • Technical input and prototypes supporting funding or innovation bids

Knowledge-graph based systems

The application of knowledge graphs as the primary data and memory layer for intelligent systems such as AI agents. KGs preserve detailed semantic information, i.e., the nature of relationships between entities.

  • Ontology and schema design aligned to domain requirements
  • Entity and relation extraction from text and semi-structured sources
  • Graph construction and consolidation
  • Integration with LLMs for semantic retrieval
  • KGs as foundation for memory for agentic-AI systems

Example applications include multimodal data fusion, data retrieval with reduced hallucinations, recommendation systems, cross-system relationship discovery, domain-independent data workflows.

Knowledge graph schematic

LLM workflows and agents

The design and implementation of language model systems and autonomous agentic systems that combine tool use, retrieval from knowledge bases, task-planning, and integration with external APIs and data sources.

  • Chain-of-thought reasoning patterns for explainability
  • Tool-calling architectures and function integration
  • Retrieval-augmented generation from vector and graph stores
  • Multi-step reasoning workflows and autonomous agent orchestration
  • Privacy preserving architectures

Example applications include multilingual retrieval systems with reduced hallucinations and autonomous LLM-based agentic systems.

LLM characteristics

Graph machine learning

The application of graph neural networks and relational learning methods to enable predictions, anomaly detection and relationship analysis across connected entities.

  • Link prediction, temporal link prediction, node and edge classification
  • Explainability methods
  • Geometric graph representation learning for massive datasets
  • Hybrid knowledge graph + graph ML methods
  • Graph representation of physical and digital system topologies

Example applications include predictive maintenance systems for physical assets and manufacturing, and supply chain risk analysis.

Graph machine learning pipeline diagram

Embodied and agentic systems

Development of autonomous agents operating in physical or simulated environments, combining perception and execution for tasks requiring spatial reasoning and physical interaction. From LLMs to vision-language-action models (VLAs).

  • Perception pipelines for sensor fusion (vision, lidar, audio)
  • Deployment of physical platforms and real-world testing
  • Integration with platform specific low-level autonomous capabilities
  • Human-machine teaming: Human-in-the-loop and human-on-the-loop systems
  • Seamless human interaction with complex engineered systems

Example applications include inspection robotics and search-and-rescue systems.

Embodied agent system control

Technical Direction & CTO Support

Work in this area focuses on creating and instantiating an effective technology development & innovation strategy for a specific goal. We provide structured technical direction for innovation, which enables to move initial ideas into demonstratable products or create new hands-on capability. This operates alongside existing leadership structures including CEOs, CTOs and R&D heads.

The scope includes evaluation of current technical capabilities, identification of feasible pathways, opportunities and risks, aligning teams and methods, and support for architectural and organisational decisions.

Focus areas

  • Assessment of current technical and organizational capability
  • Identification of capability gaps, constraints and development pathways
  • Team structure & roles assessment and alignment
  • Integration of new capability into existing systems
  • Guidance on technical hiring priorities
  • Enhancement of technical credibility

T0 Capability Assessment

Evaluation of current system state, identification of strengths, weaknesses and constraints, and recommendations for technical direction, depending on goals.

  • Architecture review & components assessment
  • Workflow & team review
  • Technology vs. business needs assessment
  • Technical deep dive
  • Innovation proposal for new technical capability

Alignment of Team & Technology

Setting the foundations for growth for the technical team and product.

  • Hands-on embedding in the technical team
  • Goal alignment across the team
  • Establishing an agile sprint rhythm with clear responsibilities and best practice day-to-day workflows
  • Defining immediate and future priorities
  • Restructuring the technical product architecture to align with team and goals
  • Preparation for specific external-facing opportunities

Ongoing Strategic Leadership

Periodic involvement at leadership level to provide input on technical direction and major technical decisions.

  • Supporting critical technical decisions
  • Review of risks, challenges and opportunities
  • Support during hiring and programme shaping

Demo Excellence & High-Stakes Readiness

Demonstrations often form the basis for internal decisions, external communication, or funding discussions. We focus on preparing clear, coherent demonstrations from existing prototypes, to deliver credibility when it counts.

Work includes auditing the current demo stack, stabilising dependencies, reducing unnecessary complexity, clarifying the core storyline, preparing runbooks and fallback procedures. Technical presentation and framing form part of the work where relevant.

From internal prototype to reusable asset

Current state

Fragile internal prototype or partial story, with dependencies on team members and manual interventions.

Prepared demo

Stable, coherent configuration ready for presentation with documented setup, clear narrative and fallback procedures.

Reusable asset

Maintained internal artefact that can be reliably deployed for multiple audiences rather than a single-use demonstration.

Typical scenarios

short-term

Time-constrained stabilisation

Rapid preparation of a demonstration under tight deadlines, focusing on core functionality, environment stability and narrative clarity.

programme-level

Flagship demo design

Development of a signature demonstration for recurring use, including technical architecture, presentation materials and maintenance protocols.

ongoing

Demo-as-a-product practice

Establishment of internal processes for treating demonstrations as maintained products, with version control, testing and documentation standards.

leadership

Technical presentation support

Direct presentation of technical systems to executive or external audiences and boosting technical credibility for the demo.

Policy Cards & AI Governance

We support organizations developing their AI governance systems. Policy Cards provide machine-readable control and governance for autonomous and intelligent agentic systems. They enable a clean separation between AI engineering and AI governance roles & responsibilities in organizations.

Application domains, pilot programmes and implementation support are detailed below.

Policy Cards form the pillar for AI Governance.

View Policy Cards

How engagements are structured

Engagements are scoped with defined objectives, and concrete outputs. Formats vary depending on whether the work involves research, prototyping, decision support, or demonstration preparation.

At the core of all engagements is our meticulous focus on understanding the goals and value adding opportunities. We emphasise compactness, precision of outputs, and a balance between formal goal-setting and direct, informal communication that keeps work aligned and hands-on throughout the engagement.

Engagement formats

Selected projects may incorporate collaborators in machine learning, physics, robotics or domain-specific fields, depending on scope.

Initiate a conversation

We invite you to get in touch to discuss your goals and explore which technical directions may be appropriate to support them.