iGeekx
Services

Five things we do well.

Each service ships with documentation, tests, and a runbook. Engagements are scoped to deliver something useful in weeks, not quarters.

01 / Service

AI Workflow Automation

Turn manual operations into AI-assisted workflows that run themselves.

LLMsWorkflow toolsQueuesWebhooks
TIMELINE: 2–4 weeks
Ideal use cases
  • Inbox triage and reply drafting
  • Document classification and routing
  • Lead enrichment and qualification
Handoff deliverables
  • Workflow design + guardrails
  • Tool integrations
  • Logging and human-in-the-loop
  • Runbook and handoff
Business outcome
Repetitive work happens on its own — with humans in control where it matters.
02 / Service

Custom AI Agents

Focused agents that do one job well — with tools, memory, and guardrails.

LLMsTool useVector DBEval harness
TIMELINE: 3–6 weeks
Ideal use cases
  • Support assistants grounded in your docs
  • Internal copilots for ops and sales teams
  • Research and outreach agents
Handoff deliverables
  • Agent scope + tool contracts
  • Evaluation suite
  • Observability for every call
  • Operator dashboard
Business outcome
An agent your team trusts because you can see exactly what it does.
03 / Service

RAG & Knowledge Systems

Retrieval pipelines that actually answer — with citations and freshness.

Vector DBEmbeddingsRe-rankersPostgres
TIMELINE: 3–6 weeks
Ideal use cases
  • Internal knowledge search across docs and tickets
  • Customer-facing answer bots
  • Compliance-aware Q&A
Handoff deliverables
  • Ingestion + chunking pipeline
  • Retrieval + re-ranking
  • Citations and eval suite
  • Access control
Business outcome
Your team and customers get grounded answers, not plausible-sounding guesses.
04 / Service

AI-Powered Applications

Full applications with AI woven into the product, not bolted on.

ReactFastAPI / NodePostgresModel gateways
TIMELINE: 4–10 weeks
Ideal use cases
  • AI-native SaaS features
  • Internal tools with embedded copilots
  • Customer-facing AI dashboards
Handoff deliverables
  • Product + AI architecture
  • UI, API, and model layer
  • Cost + rate-limit controls
  • Deployment + monitoring
Business outcome
A real product with AI features your users can rely on day after day.
05 / Service

AI Infrastructure & Glue

The integrations, queues, and observability that keep AI features alive in production.

Model gatewaysQueuesPostgresObservability
TIMELINE: 2–4 weeks
Ideal use cases
  • Model gateways with routing and fallbacks
  • Background jobs for long-running AI tasks
  • Logging, evals, and cost dashboards
Handoff deliverables
  • Reference architecture
  • Provider routing + retries
  • Cost + usage dashboards
  • Incident runbook
Business outcome
AI features that don't fall over when traffic, models, or providers change.

Not sure which fits your situation?

A 30-minute discovery call resolves it. No commitment.

Book a Free Discovery Call
Start QuizBook a Call