AI services

AI services that ship into real workflows

We design, build and integrate AI where it removes real work: answering customers, finding answers in your documents, and moving routine tasks off people’s desks.

Start with the job to be done, then choose the model

Most AI projects stall because the use case was vague, the data was not ready or nobody measured the result. We begin with one workflow, define what a good outcome looks like, and build the smallest system that proves it before widening the scope.

  • A clear use case

    We pin down who uses it, what it replaces and how success will be measured.

  • Systems, not demos

    Evaluation sets, guardrails, logging and fallbacks are part of the first release.

  • Built to improve

    We review real conversations and failures after launch and tune from them.

What we build

AI agents

Agents that take a request, use your tools and APIs, and finish the task or hand it to a person with the context attached.

Chatbots and assistants

Website and in-app assistants that answer from approved content, collect details and escalate cleanly.

Retrieval over your documents (RAG)

Search and answers grounded in your own files, wikis and tickets, with citations people can check.

Workflow automation

Document handling, triage, classification and routing that runs in the background and flags exceptions.

AI strategy and use-case mapping

A ranked list of where AI will pay off in your operation, with effort, risk and a first pilot defined.

Integration

Connecting models to your CRM, helpdesk, calendar, database or internal API so the output lands where work happens.

How an AI project runs

  1. Frame the use case

    One workflow, one owner, a measurable target and a list of the data involved.

  2. Prototype on your data

    A working version in days, tested against real examples rather than invented ones.

  3. Build and integrate

    Production code, authentication, your systems connected and the edge cases handled.

  4. Evaluate and harden

    A test set, red-team prompts, cost and latency budgets, and clear human handoff rules.

  5. Launch and monitor

    Staged rollout with dashboards for quality, usage and spend.

  6. Improve

    Regular review of real interactions, with fixes shipped in small releases.

Why teams work with us on AI

We run our own AI product

Basalix AI answers live phone calls and web chats for law firms. We know what it takes to keep AI reliable in front of real customers.

Provider-neutral

We pick models and vendors on quality, cost and data requirements, and design so you can switch later.

Honest about fit

If a rules-based fix or a simpler tool does the job, we will say so before you spend on AI.

Our product

Basalix AI: an AI front desk for law firms

Basalix answers the phone line and website chat around the clock, screens each inquiry on the attorney’s own criteria, books consultations into real calendar availability and delivers the lead to the firm’s CRM.

  • Voice and web chat agents, in English and Spanish
  • Screens on the firm’s own intake criteria
  • Books consultations into live calendar availability
  • Delivers each lead to the firm’s CRM

Frequently asked questions

How long does a first AI project take?

A focused pilot, such as a support assistant over your documentation or a triage agent for one inbox, usually reaches a working version in two to four weeks. Production hardening and integrations add to that depending on the systems involved.

Can the AI answer only from our own content?

Yes. We build retrieval so answers are grounded in the documents you approve, show their sources, and decline or escalate when the content does not cover the question.

Which models do you use?

We choose per project from the leading commercial and open models, based on accuracy on your examples, cost, latency and where your data is allowed to go. The design keeps the model swappable.

Do you keep working on it after launch?

Yes. Most clients keep a light monthly engagement for monitoring, prompt and retrieval tuning, and new use cases built on the same foundation.

Have a workflow you think AI could handle?

Describe it in a few lines. We will tell you whether AI fits and what a first pilot would look like.