AI that answers from your data — and shows its work.

Retrieval-augmented assistants, agents and automations built on the systems you already run — with evaluation, guardrails and cost controls designed in from day one, not bolted on after the demo.

Book an AI readiness workshop Engagement models

YOUR SOURCESRETRIEVEGENERATEVERIFY

What's the carryover rule for unused PTO for our remote staff?

[1] HR Handbook · Confluence[2] PTO Policy 2026 · SharePoint

CITATIONS CHECKEDPII FILTER ONACCESS: HR GROUP

SOUND FAMILIAR?

The demo was great. Production is another story.

Knowledge locked in wikis, drives and inboxes.

People ask the same five experts the same questions every day. An assistant grounded in your documents answers first — with sources.

Pilots that never reach production.

Security, identity, logging and cost control are what stop pilots. We build those first, so the pilot is already production-shaped.

No way to tell if the answers are right.

We build a test set from your real questions and score every release against it, the same way we'd test code.

What we deliver

Azure OpenAI · Anthropic · LangChain · LangGraph · MCP · n8n · Azure AI Search · pgvector · Python

Knowledge assistants

RAG over Confluence, SharePoint, Google Drive and ticketing systems, respecting each user's existing permissions.

Agentic workflows

Multi-step agents that research, draft and act across your tools — with a human approval step wherever it matters.

Process automation

Intake, triage, document extraction and routing with n8n, Power Automate or Azure Functions.

Engineering copilots

Assistants wired into Azure DevOps through MCP tools — pipeline triage, drift detection, release notes, bug-fix suggestions.

Evaluation & guardrails

Golden test sets, citation checks, PII handling and red-team prompts, run on every change.

Platform & cost control

Model selection, private networking, usage monitoring and spend caps, so finance never gets a surprise invoice.

SELECTED WORK

AI we built for our own engineering teams first.

MULTI-AGENT ASSISTANT

Hundreds of DevOps docs, one question box

A LangGraph supervisor routing to Confluence, Key Vault and DevOps agents, so engineers get answers with sources instead of searching the wiki.

SECRET TRACING

Find where a secret went missing

The same assistant traces each secret from Key Vault into Databricks secret scopes and points to the exact step where it was lost.

AI-ASSISTED OPERATIONS

Agent skills for the jobs nobody likes

Cursor agent skills that break stuck storage leases after failed pipelines, back up Databricks scopes and Key Vaults, and run pre-deployment readiness checks.

ENABLEMENT

Teams trained to keep it running

Hands-on training for engineers in DevOps, Python and AI-assisted development, so the tools outlive the engagement.

How we work

01 · WORKSHOP

Pick the right problem

Rank candidate use cases by value, data readiness and risk. Leave with one worth building.

02 · PROVE

Prove it on your data

A working pilot with real users, scored against a test set you helped write.

03 · PRODUCTIONIZE

Harden and ship

Identity, logging, guardrails and CI/CD, deployed into your own cloud tenant.

04 · OPERATE

Measure and improve

Monthly quality and cost reviews, new sources and new skills as adoption grows.

Engagement models

FIXED SCOPE

AI Readiness Workshop

Use-case ranking, data and security review, and a costed roadmap your leadership can approve.

$2,5001 day · on-site or remote

MOST CHOSEN

Production Pilot

One use case built end to end on your data, evaluated, secured and live for a real user group.

$12,0004–6 weeks · fixed price

RETAINER

AI Program

A standing team that operates what's live and ships the next use case each quarter.

$4,000 / monthModel usage billed at cost

Questions

Find the one AI project worth doing first.

Bring your shortlist. We'll tell you which one your data can actually support.

Book a discovery call webologist@enterprisesoftware.biz (706) 832-9632

PAIRS WELL WITHES-01 · Azure DevOps ES-02 · Web Applications