Each one is scoped to a real workflow, wired into real systems, and measured against real cases before it goes live.
Agents that answer customer and internal questions from your real systems — docs, help center, order data, CRM. They pull live context, take action (refund, reschedule, update a ticket), and escalate to a human with a full summary when confidence is low.
Multi-step back-office work handled end to end: intake a request, validate it against policy, update three systems, chase the missing field, and close the loop. Built for the messy processes that rules engines and RPA scripts break on.
Agents that ingest large, messy document sets — contracts, filings, clinical docs, RFPs, research — and produce a sourced report or a precise answer. Every claim traces back to the page it came from, so your team can verify instead of trust.
Long-running agents wired into your repos, internal docs, Jira and logs. Give it a ticket: it reproduces the issue, reads the relevant code and recent changes, correlates with error traces, writes the fix plus tests, and opens a PR with its reasoning attached. Minutes of work, not seconds — because the problem deserves it.
Agents that pull spend and performance across Meta, Google, TikTok and LinkedIn, compare it against your historical knowledge base of what worked, and return concrete recommendations — shift budget here, kill this creative, this audience is fatiguing. With approval, they execute the change.
Most valuable agents are specific to one company. We start from the workflow, not the model — map the decisions, find where judgment is actually needed, and build an agent that fits how your team already works.
Anyone can get an agent working once. The engineering is in making it work on the two-hundredth run, with money and customers on the line.
The agent gets real access — your repos, tickets, docs, dashboards, databases. Scoped credentials, least privilege, your infrastructure.
It plans a sequence of steps, gathers what it needs, and revises when reality disagrees with the plan. Long-horizon runs, not single prompts.
Tool calls with typed inputs and hard guardrails. Reversible actions run free; irreversible ones wait for approval you configure.
Every agent ships with an eval suite built from your real cases. We measure task success before launch and track regressions after.
Full traces of every run — inputs, tool calls, cost, latency, outcome. When something goes wrong you see exactly which step did it.
Claude (Anthropic) · GPT · Gemini · open-weight models on your infra
Claude Agent SDK · MCP · LangGraph · custom orchestration · TypeScript & Python
pgvector · Pinecone · Weaviate · LangSmith · Langfuse · OpenTelemetry
We are model-agnostic and route per task — reasoning-heavy steps to the strongest model, high-volume steps to the cheapest one that passes evals. You are never locked to one vendor.
No bureaucracy. No science project. An agent doing real work in weeks.
Most agent projects die in the gap between an impressive demo and a system you would trust with a customer. We close that gap by building an eval suite from your real historical cases before we build the agent — so "is it good enough?" becomes a number you can look at.
Running on your real data and real tasks. Not a slide deck, not a sandbox demo.
Talk to the engineer building it, not an account manager. Decisions in hours.
Typed tools, approval gates on irreversible actions, spend caps, full audit trail.
One workflow or a fleet of agents — flexible, milestone-based payment terms.
Code, prompts, evals, infra config. Repo access from day 1. No platform lock-in.
Automation and AI running in production, serving real users
We built the core engine — continuously discovering copay assistance programs across dozens of sources, tracking real-time open/close status so patients only ever see active programs, and automating enrollment end to end with an outcome dashboard. HIPAA-compliant throughout.
Visit getcopayhelp.comProperty matching platform that reads buyer intent in natural language, reasons over listing data and preferences, and surfaces the handful of homes that actually fit — instead of another filtered list.
Visit browndoor.aiOur founder contributed as a Senior Developer on one of the world's largest e-commerce marketplaces — building features and backend systems powering millions of transactions.
Visit groupon.comHear directly from the founders and leaders we've worked with
Mayukh built GetCopayHelp — a HIPAA-compliant platform helping US patients access $0 copay prescriptions. He shares his experience working with our team on the automation engine behind it.
We've seen every one of these. They are all solvable.
Sound familiar?
This is exactly the work AgentixWorks does.
Everything you need to know before you start
Still have questions?
Get in touch with our teamBring us one painful workflow. We'll tell you on the call whether an agent is the right answer — and if it is, you get a working one in two weeks.