AI & Automation
Practical automation and AI-assisted workflows: orchestration between tools, guarded LLM features, and internal systems that reduce manual work. We scope pilots honestly and design for review, logging, and rollback—not magic demos.
Who this is for
Operations and product teams drowning in copy-paste between SaaS tools, or adding model-backed features to an existing product. Delivery from our San Diego studio with hybrid or fully remote collaboration.
Common use cases
- Ticket or lead triage with human-in-the-loop
- Scheduled reporting and data sync between systems
- Document Q&A over private corpora with access control
- Replacing brittle scripts with maintainable services
What you get
Clear scope, technical accountability, and delivery momentum from kickoff through launch.
- Workflow automation between CRM, support, finance, and custom systems
- AI features behind guardrails: classification, drafting, retrieval over your docs
- Internal tools that combine human judgment with model output
- Integration design with rate limits, idempotency, and failure handling
Typical deliverables
Workflow discovery · Architecture and security review · Build and integration · Monitoring and iteration.
How we work
- 1Start from one concrete workflow with measurable time saved.
- 2Define success, failure modes, and who approves automated actions.
- 3Ship narrow, observable components before expanding scope.
Pilots that survive compliance conversations
Model-backed features belong behind auth, logging, and human approval when outputs can commit money or customer promises. We scope pilots so security and legal can review a bounded surface—not an open-ended “AI everywhere” mandate.
Related case studies
Deeper delivery stories—not one-line portfolio blurbs. Each links to full narrative and scope.
Related services
Common questions
Straight answers—how we scope, deliver, and support production software.
When is automation or AI the wrong answer?
When the process is undefined, data quality is poor, or nobody owns approvals. We narrow to one workflow with clear success criteria before expanding—so you do not automate chaos.
How do you handle security with LLMs and integrations?
Access control, logging, human-in-the-loop for sensitive actions, and rate limits are part of design—not extras. Pilots stay small and observable before broad rollout.
Can you automate between our SaaS tools and custom systems?
Yes. We build durable connectors and idempotent jobs so retries and failures are safe—whether the glue is rules-based, API-driven, or model-assisted with guardrails.
More proof
Browse the full case study collection or the complete project archive.
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