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Use-case scoping
Two-week scoping engagement. We define the workflow, build a real eval set, and propose an architecture.
Workflow AI that earns its keep.
We’ve packaged the patterns we use again and again (document extraction, ticket triage, contract review, internal copilots) into a solution accelerator that takes you from idea to production in 6–10 weeks.
What AI Automation covers.
AI Automation is our solution accelerator for the AI use cases that show up in almost every business: document understanding, agent-driven workflows, internal copilots, and ticket-triage automation. The foundations (retrieval, evaluation, observability, and fallback) are already built, so the work can focus on configuring your specific workflow. You see value sooner, with the same engineering standards.
Where it helps most
Document-heavy operations
Claims, contracts, SOWs, applications, and regulatory filings: anywhere people read documents and pull out structured data.
Internal copilots
Customer support, sales enablement, and IT helpdesk teams, where employees spend time looking up information.
Ticket triage
Inbound classification, prioritization, and routing for support, sales, or operations queues.
Process automation
Multi-step workflows where AI agents can replace or accelerate human-in-the-loop steps.
What we deliver.
Each item below is a concrete deliverable that we scope, build, and stay accountable for.
Document intelligence
Layout-aware extraction, table understanding, multi-document reasoning, and structured output validation.
Agentic workflows
Bounded-action agents with dry-run mode, audit logging, and human-in-the-loop checkpoints.
Internal copilots
RAG-powered assistants over your documentation, runbooks, or product data with eval-tested response quality.
Triage & classification
High-volume classification with active learning, confidence scoring, and human-review queues.
Eval & observability
Eval suite, regression detection, and the dashboards that show whether the AI is actually working.
Safe AI patterns
PII redaction, prompt injection defense, response filtering, and the safety patterns that keep enterprise AI deployable.
How an engagement runs.
Five phases, each with outcomes we can measure.
Why work with us.
An accelerator plus the engineering
We don’t leave you with a templated app. The engagement includes the engineering work to integrate with your stack.
Eval-driven from sprint zero
Every workflow ships with a measurable eval set. If it can’t be evaluated, we won’t build it.
Production patterns, not demos
Our accelerator includes observability, safety, and operations, not just a happy-path demo.
Frequently asked questions.
Still unsure? A 30-minute call with a tech lead answers the rest.
Ask us directlyHow is this different from buying an off-the-shelf AI tool?
Off-the-shelf tools work for generic use cases. Our accelerator gets you the speed of a tool with the customization of an in-house build. We deploy to your cloud, integrate with your stack, and you own the result.
Do you support on-prem or air-gapped deployment?
Yes. We’ve deployed AI workflow accelerators in air-gapped and on-prem environments using self-hosted Llama and Mistral models.
What models do you use?
We’re model-agnostic and choose what fits your latency, cost, and compliance constraints: OpenAI, Anthropic, Bedrock, Vertex, Azure OpenAI, or self-hosted.
How do you measure ROI?
We define 2–4 outcome metrics at scoping (cycle time, error rate, cost per transaction, deflection rate) and track them in dashboards through and past launch.
What happens after you leave?
Documentation, runbooks, and a structured handoff. Your team owns the deployed workflow. Optional retainer for monthly model upgrades and eval maintenance.
Let’s talk about your project.
Tell us about your team, your stack and the problem you want solved. We’ll come back with how we would approach it.
Response time
Within one business day
Prefer a call?
Headquarters
Charlotte, North Carolina
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