Conversational AI agents
Multi-turn support and sales agents that resolve tickets end to end, escalating to humans with full context instead of a transcript dump.
Services
AI Solutions
AI that resolves work, not just answers it
We design, build and operate AI systems on your own data — agents that take actions, retrieval that cites its sources, and evaluation so you know it still works next quarter.
- Custom AI agents trained on your data
- Success criteria agreed before the build
- Human escalation with full context
- Evaluation suite so quality is provable
- Private or on-prem deployment
What this engagement covers
Scoped to your situation — we start with what you already have rather than a fixed package.
RAG over your data
Retrieval pipelines across documents, tickets and databases with citations, freshness controls and permission-aware access.
Workflow automation
Agents wired into your CRM, ERP and helpdesk so they can actually update records, not just describe what should happen.
Evaluation & guardrails
Golden datasets, regression suites and hallucination checks so model or prompt changes never ship blind.
Model strategy
Benchmarks across frontier and open models against your real workload, balancing cost, latency and accuracy.
Private deployment
Run inside your VPC or on-prem when data residency, procurement or compliance requires it.
Our AI services
Each service is purpose-built — click through to see how we deliver it.
Small first, then scale what works
Six stages, with a decision point after the pilot. Nothing grows until it has shown value.
01
Workflow Audit
Understand the current manual process, systems, users, inputs and outputs.
02
Architecture
Choose the smallest practical automation architecture.
03
Pilot
Build one usable workflow.
04
Integration
Connect APIs, browser workflows, internal tools, databases, AI models or third-party systems.
05
Validation
Test reliability, edge cases, user approval and expected output.
06
Scale
Expand only after the pilot demonstrates value.
What you get
- Use-case audit with agreed success criteria
- Working prototype on your data, typically within a few weeks
- Production deployment with monitoring and evaluation harness
- Runbook and team handover so you are not dependent on us
Tools we reach for
Chosen per project, not per habit. If your team already runs something that works, we build on it.
- Claude
- OpenAI
- LangGraph
- Vercel AI SDK
- pgvector
- Pinecone
- Python
- TypeScript
FAQ
AI Solutions — common questions
No. We use provider API tiers and settings that exclude your data from model training, and where the workflow requires it, systems can run on private infrastructure or self-hosted models.
Other things we build
Have a workflow in mind?
Tell us about the process. We'll review it and suggest the most practical next step.