WHO IT'S FOR
- Product teams adding LLM features to an existing application.
- Operations teams with document-heavy or repetitive workflows.
- Leaders who want AI designed around real tasks, real data, and production constraints.
PROBLEMS IT SOLVES
- 01
AI features need to work with real data and production constraints, not just in a demo.
- 02
Automated work still needs people to approve what matters.
- 03
Documents and workflows that slow the business down.
Approach. People approve what the system proposes.
- 01 Data Start from the real data the task depends on.
- 02 Model Choose and integrate the model that fits the job.
- 03 Workflow Fit the AI into how work actually gets done.
- 04 Human review People check and approve before results are used.
WHAT YOU GET
- LLM features
- Agents
- Document processing
- Workflow automation
ENGAGEMENT MODEL
An outcome
Managed Software & AI DevelopmentChoose this when you need something built. GTG scopes the work, assembles the right specialists, and stays accountable for delivery. Engagements can shift as the work changes.
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Questions
- Who is accountable for AI output?
- People. Workflows are designed with human checkpoints so the system proposes and people approve.
- Do you also use AI to build software?
- Yes — AI in what we build and in how we build. AI-assisted development speeds up iteration, while engineers stay accountable for architecture, code quality, testing, privacy, and security.