Services
Custom AI engagements built on infrastructure you own — data substrate, agent runtime, and eval discipline, designed for your team. Model-agnostic and self-hostable. Want a packaged version instead? See Products → Each service stacks; start anywhere, grow into the rest as the work demands it.
AI Readiness & Roadmap
A fixed-scope assessment that maps your data, systems, and workflows — and returns a concrete plan for the first AI system worth building, with the governance to run it safely.
Data Foundations
One trusted set of data your dashboards, your AI, and your agents can all read. Clear owners, freshness targets, and access controls from ingest to query.
Data Lake & Lakehouse
The storage and ingestion sub-service under Data Foundations. A lakehouse on open table formats with streaming and CDC ingestion, lineage, dead-letter handling, and retrieval indexes. One substrate for analytics, AI, and operational tools.
AI Platform
One operating layer for the AI models, tools, and data your teams use. Cost, quality, and governance you can see. Provider choices — hosted, local, or self-hosted — you can change without rewriting the system.
MCP & Agent Readiness
Make your systems callable by Claude, ChatGPT, and the agent ecosystem — MCP servers over your APIs with real authentication, published discovery surfaces, and governance over which agents may do what.
Agent Workflows
AI agents that act on business events with the tools, memory, approvals, and traces you can audit. Workflows that ship to production, not just demos.
AI Assistants
Assistants your team and your customers can trust: grounded in your documents and records, aware of permissions, able to take approved actions — in chat, in your tools, or on the phone.
AI Dashboards & Reporting
Dashboards you build by asking. Describe the chart you want in plain language, get it from governed data, pin it — and it keeps itself up to date. Reporting becomes a conversation, not a backlog ticket.
Benchmarks
A test set built from your production traffic that catches AI regressions before they ship. Prompt or model changes have to pass quality, latency, cost, and safety thresholds before users see them. Requires production traces to draw from.
Conversation Intelligence
Every conversation your customers and teams have — across support, email, chat, messaging, and voice — turned into signal you can act on: what's breaking, what's selling, what to fix, what to ship next.
LLM-Ready Knowledge Base
A company knowledge base built from your actual data sources — documents, tickets, code, conversations, structured records — chunked, embedded, permissioned, evaluated, and kept fresh on AWS so AI systems can cite real answers instead of guessing.
Self-Optimizing Agents
An optimization loop that proposes variants of your AI workflows — different prompts, models, retrieval, tool budgets, even generated code — and only promotes the ones that improve under quality, latency, cost, and safety gates.
Embedded Agents
An AI agent that lives inside your website, app, or voice line — with the persona, knowledge, and tools you approve, and a real outcome for every conversation that doesn't end in a clean answer.
Engagement Model
How working with us is shaped: a fixed-scope assessment, a staged build with eval gates, and a transfer that ends with your team owning the system. No per-seat licenses at any stage.