Even in agile organisations, discovery and implementation happen in phases. Business context is richest during planning sessions. But by the time developers build, that context has already started to fade. Decisions need re-interpretation. Technical questions wait for the next refinement. This gap between knowing and doing is where projects slow down.

Solita CollabAI™: Real-time clarity that compounds

CollabAI brings decision-makers, domain experts, and developers into the same room, working in real time with AI. Business logic, constraints, and technical decisions get captured as structured, machine-readable context as they emerge. No translation layer. No handoff delay.

What this means:

• Accelerated discovery: Know what to build in weeks, not months – business decisions turn into actionable specs immediately.

• Specs that stay fresh: Domain experts shape requirements directly; agents implement what was agreed while context is still warm.

• Knowledge that compounds: Every session adds to your Shared Context Library – domain models, decision logs, and specs that persist beyond individual projects.

• Plugs into your process: Works with your tech stack, output formats, and governance – without replacing your existing workflows.

Who benefits:

• Business stakeholders: Ideas become working prototypes in weeks.
• Developers: Less time interpreting vague requirements, more time solving real problems.
• The organisation: Context doesn’t reset with every project – it compounds.  

Interested? Talk to our experts 

Raw data shows “Customer ID 47281 purchased SKU 9204.” Your semantic layer reveals “High-value enterprise customer renewed premium service during competitor promotion.” We turn data and requirements into a shared, managed context that powers agentic AI from ideation to deployment.

Move beyond PowerPoint-driven decision making

Traditional documentation creates layers of interpretation where objectives get lost in translation from strategy to execution. A living knowledge base enables decisions and objectives to flow from portfolio level to team level – understood by both humans and agents – without loss of meaning.

What this means:

• An evolving single source of documentation for humans and agents
• Every solution domain reads from and writes back to the library, compounding domain and technology knowledge over time
• Includes your domain logic, regulatory requirements, and operational workflows
• Eliminates the translation gap between strategic intent and operational execution

Interested? Talk to our experts 

We help organisations leverage agent technology comprehensively, from the individual level to organisation-wide transformations. These levels are interdependent: individual capability enables process change, embedded agents require AI-literate users, and team-level transformation builds on both.

Personal level agents

Personal agents represent a step-level change in what individuals can do. Instead of fixed functions and predefined workflows, agents adapt to the specific problem at hand. Someone can spin up a custom analysis, create a specialised tool, or model a complex scenario on the fly, simply by describing what’s needed. The more one understands what’s possible, the more powerful they become.

Process-embedded agents

Embed agents into workflows, automations, and systems. Deeply integrated capabilities transform how work flows through your organisation.

What this requires:

• Rethinking processes from an AI perspective
• Changes in organisational roles
• Moving from PowerPoint-driven decisions to a shared context that both humans and agents can act on

Agent teams for development

Create a “small scrum team” with specialised agents for software development.

When developers have access to shared context and shared tooling, work shifts from the individual level to the team level. Agents and humans operate over the same artefacts—code, tasks, documentation. Task management, ticket creation, and many other activities can happen as part of agentic workflows.

What this means:

• Specialised agents (tester, developer, architect, security) working together
• Task management and prioritisation partly handled by agents
• Developers gain access to the entire team capabilities 

Interested? Talk to our experts 

AI transforms software development when it operates within structure: established practices, architectural patterns, and organisational context. We bring software engineering discipline to agentic development—turning conversations into production-grade code that integrates with your existing systems.

From conversation to code with engineering rigor

Agentic development isn’t about letting AI freestyle. It’s about channelling AI capability through proven software practices: version control, testing strategies, architectural patterns, and integration standards. We adapt language models to your specific environment—your tech stack, coding conventions, and quality requirements—so agents produce code that fits, not code that needs rewriting.

Structure over vibes

Strong engineering practices become even more critical with AI agents. We ensure proven practices translate to agent-generated code through adapted code review protocols, testing frameworks, and architectural patterns. Agents work through controlled integration points, respecting API contracts, data schemas, and system boundaries. Your organisational knowledge, domain logic, and technical constraints flow to agents through shared context, guiding what they build.

What this means:

• Disciplined acceleration: Speed comes from structure, not shortcuts.
• Integration-ready: Agents respect your system boundaries and architectural decisions.
• Context that compounds: Organisational knowledge flows to agents through shared context.
• Quality at speed: AI reviews every commit for patterns, security issues, and architectural consistency.
• Expertise multiplied: Senior knowledge becomes accessible to the entire team through agents that understand your codebase and conventions.

Interested? Talk to our experts