Agentic AI that does the work, grounded in your data.

We design, build, and run AI agents and retrieval-augmented systems for healthcare, financial services, telecommunications, and education, with security, evaluation, and human oversight built in from day one.

Illustration of a friendly AI agent orchestrating documents, data, security checks, and messages
What we build

Agentic AI, built for your industry.

Agents that finish the work

Agentic AI & workflow automation

AI agents that go beyond chat. They break a goal into steps, call your systems through secure tools and APIs, check their own output, and hand off to a person whenever a decision needs approval.

We build single agents for focused tasks and multi-agent systems for longer workflows, integrated with the applications your team already uses.

  • Multi-step agents with tool and API use
  • Human-in-the-loop approvals and escalation
  • Integrations with CRM, ERP, EHR, ticketing, and email
  • Full activity logs for every action an agent takes
Retrieval-augmented generation

RAG environment creation

A retrieval-augmented generation (RAG) environment lets AI answer from your own documents and data, with citations, instead of guessing. It is the foundation for trustworthy assistants and agents.

We stand up the complete environment: connectors, document processing, embeddings and vector search, permission-aware retrieval, and an evaluation harness to measure answer quality.

  • Connectors for SharePoint, drives, databases, wikis, and PDFs
  • Chunking, embeddings, vector search, and reranking
  • Permission-aware retrieval that respects user access
  • Answer-quality evaluation and monitoring dashboards
Clinical & administrative AI

AI for healthcare systems

AI that reduces the administrative load on clinicians and staff: summarizing charts, drafting documentation, preparing prior-authorization packets, and answering policy questions from approved sources.

Architectures are designed around protected health information: data stays in your environment, access is role-based, and every output can be reviewed before it is used.

  • Visit and chart summarization for review
  • Prior-authorization and referral packet preparation
  • Patient intake, scheduling, and message triage
  • PHI-aware design: redaction, access control, audit trails
Banking, insurance & finance ops

AI for financial systems

AI for document-heavy financial work: extracting data from statements and applications, assisting KYC and AML reviews, reconciling transactions, and answering questions from policy and product documentation.

Models run behind your controls, with explainable outputs, reviewer sign-off, and the audit evidence regulated teams need.

  • Document intelligence for statements, invoices, and forms
  • KYC and AML review assistants
  • Reconciliation and exception-handling agents
  • Underwriting and claims triage support
Network, care & operations AI

AI for telecommunications

Agents that help network operations teams triage alarms, correlate incidents, and draft resolution steps from your runbooks, and that help care teams resolve billing and service questions faster.

We integrate with OSS/BSS, ticketing, and knowledge systems, and keep engineers in control of every network change.

  • NOC copilots for alarm triage and incident summaries
  • Customer care and billing-dispute agents
  • Order, provisioning, and number-porting automation
  • Knowledge assistants for field technicians
Colleges, universities & schools

AI for educational institutions

Assistants that answer student questions about admissions, financial aid, registration, and policies around the clock, grounded in your catalog and handbooks, plus agents that process transcripts, forms, and enrollment documents.

Built with student-privacy (FERPA-aware) controls, role-based access, and staff review for anything that affects a student record.

  • 24/7 admissions and student-services assistants
  • Transcript, form, and enrollment document processing
  • Advising and early-alert support for student success
  • Accreditation and compliance evidence assistants
Anatomy of an agent

How an ATG agent gets work done.

Agents follow a controlled loop, so every step is visible, permissioned, and reviewable.

GoalA task in plain language
PlanBreaks work into steps
ToolsCalls your apps and APIs
KnowledgeRetrieves from your RAG
GuardrailsPolicy and safety checks
ApprovalA person signs off
LogEvery action recorded
RAG environment

From scattered documents to answers you can trust.

Six stages we set up, test, and hand over, so your assistants answer from approved sources and show where every answer came from.

01ConnectDocuments, drives, databases, and apps
02PrepareClean, split, and tag content
03Embed & indexVector search with metadata
04RetrievePermission-aware search and reranking
05AnswerResponses with source citations
06EvaluateMeasure accuracy and monitor drift
AI by industry

AI products for every domain we serve.

AI for healthcare

What we build

  • Clinical documentation assistants
  • Prior-authorization packet preparation
  • Patient message and referral triage
  • Policy and formulary Q&A over approved sources
Discuss a use case
Security & governance

Responsible AI, engineered in.

Your environmentDeploy in your cloud or data center; your data is not used to train public models.
Access controlRole-based permissions carried through to retrieval and agent tools.
PII & PHI protectionRedaction and masking before data reaches a model.
Human in the loopApproval steps for any action with real-world impact.
Audit trailPrompts, sources, tool calls, and approvals logged for review.
EvaluationTest sets and quality metrics before and after launch.
Illustration of a shield and lock protecting data with a human review step
Model-agnostic

The right model for each job.

We select models and infrastructure per use case for accuracy, cost, and data-residency needs. Technologies we work with include:

OpenAI GPTAnthropic ClaudeGoogle GeminiMeta LlamaMistralAzure OpenAIAWS BedrockGoogle Vertex AILangGraphLlamaIndexpgvectorPineconeElasticsearchPythonSalesforce Einstein
How we engage

From idea to production, step by step.

01

Readiness workshop

Identify high-value use cases, data sources, and risks.

02

Proof of concept

A working prototype on your real data, measured against clear goals.

03

Pilot

A secured deployment with a real team, evaluation, and feedback loops.

04

Production & LLMOps

Scaling, monitoring, cost control, and continuous improvement.

Need AI engineers on your own team instead? Hire AI and data talent

Put AI to work on your hardest workflow.

Tell us the process you want to automate or the knowledge you want to unlock. We'll help you find the right first use case.