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AI Solutions

AI that does real work.

Custom AI agents, LLM-powered features, and answer-engine optimization, scoped to a use case and integrated with your stack. Measured against outcomes you can defend.

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AEO + AI search visibility Agents that take action Integrated into real workflows
AI Readiness Scope • Integrate • Deploy
Use Case Pick One that pays back fast
Data Wire Sources, retrieval, eval
Agent Build Tools, guardrails, prompts
Loop Ship Measure, refine, expand

Capabilities

AI scoped to one workflow.

We pick one workflow, build the model and tooling around it, and ship something that earns its place in your business.

GPT Claude Gemini Perplexity RAG

AEO + AI Search SEO

Get cited by ChatGPT, Perplexity, Claude, and Google's AI Overview. Content structuring, schema, and authority signals tuned for answer engines.

  • Answer-engine content architecture
  • Structured data + entity coverage
  • Brand mentions + citation tracking

Custom AI Agents

Domain-specific agents that read your data, call your tools, and take action: triaging tickets, drafting quotes, qualifying leads, running ops.

  • Tool use + function calling
  • RAG over your knowledge base
  • Guardrails, evals, and human-in-the-loop

AI Software + Features

Ship AI features inside your existing product or internal tools: summarization, search, generation, classification, and routing, built as production software.

  • LLM-backed APIs + endpoints
  • Streaming UIs + chat interfaces
  • Caching, cost controls, observability

Workflow Implementation

Bring AI into the workflows your team already runs in Shopify, HubSpot, Slack, Notion, Zendesk, and spreadsheets, where the work happens.

  • Workflow audits + ROI sizing
  • Integrations with your stack
  • Team training + change management

Pipeline

The AI build pipeline

We ship AI to production with a process built around evaluation, so it holds up beyond the demo.

01

Audit + Pick

Map the workflows, score them by ROI and feasibility, and lock in the first use case to ship.

Workflow mapROI sizingScope lock
02

Wire the Data

Connect knowledge sources, build retrieval, and define the eval set that sets the quality bar before we ship.

RAGEval setGuardrails
03

Build + Integrate

Build the agent or feature, integrate it into your tools, and validate end-to-end with real data and real users.

Tool useStreaming UIIntegrations
04

Measure + Expand

Track quality, cost, and adoption. Refine where it pays back, and expand to the next workflow once the first one earns.

ObservabilityCost controlsIteration

Engagements

Common Engagements

Fast Start

AEO + AI Search Sprint

Restructure content, schema, and authority signals so your brand surfaces in AI answer engines alongside classic Google.

  • AEO audit + opportunity list
  • Content + schema overhaul
  • Citation + visibility tracking
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Most Popular

Custom Agent Build

A production-ready agent for one workflow (sales, support, or ops) with tool use, retrieval, evals, and integration into your existing stack.

  • Scoped, evaluated agent
  • RAG over your knowledge base
  • Tool calls + integrations
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In-Product

AI Feature Implementation

Add a real AI feature to your product or internal tool: search, summarization, generation, classification, shipped like the rest of your software.

  • API + UI implementation
  • Streaming, caching, cost controls
  • Observability + eval harness
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Want AI that works in production?

Start with one workflow. We'll scope it, build it, measure it, then expand from there.

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FAQ

Questions, answered.

What's AEO and why should I care?

Answer Engine Optimization is SEO for AI search: ChatGPT, Perplexity, Claude, and Google's AI Overview. They cite sources differently than classic search, so the content structure, schema, and authority signals you optimize for are different too. Your brand needs to show up there if your buyers ask AI before they Google.

How do you keep AI features from hallucinating or going off the rails?

Retrieval over your real data, structured tool use instead of free-form output, an eval set that runs before every release, and human-in-the-loop on anything that touches customers or money.

Will my data train somebody's model?

No. We use API endpoints with no-training data policies (OpenAI API, Anthropic API, Gemini API). For sensitive use cases we can run open-weight models on infrastructure you control.