We build autonomous AI agents and intelligent assistants for sales, support and operations: they read, decide, call your systems and hand off to a human when it matters.
From a single assistant inside Slack to a fleet of agents working across departments, we design agents around a clear job, measurable outcomes and safe boundaries.
Agents that qualify inbound leads, research accounts, draft personalised outreach and book meetings straight into your reps' calendars.
Learn moreResolve order, billing and product questions with live lookups in your store or helpdesk, escalating to staff with a full summary.
Learn moreProcess documents, reconcile records, chase approvals and update ERP and spreadsheets without manual copy-paste.
Learn moreAssistants for your own team that answer from company docs, draft reports and run routine tasks in Slack, Teams or your intranet.
Learn moreOrchestrated agents that split complex jobs into planning, research, execution and review steps with checkpoints you control.
Learn moreSecure tool connectors, function calling, vector memory and evaluation harnesses so your agents stay accurate as data changes.
Learn moreHandles tracking, exchanges and refund eligibility via web chat and email, creating RMAs in the OMS and escalating edge cases with context.
Enriches each sign-up from public sources, scores fit against the ICP and drafts a tailored follow-up for the rep to approve.
Monitors shipment events, drafts customer updates and re-books with alternate carriers under rules the ops team defined.
An agent is only useful if it is reliable. We engineer agents the way we engineer software: scoped, tested against real cases, observable and safe to run unattended.
Allowed actions, spending limits, confidence thresholds and human approval steps are defined before any agent touches production.
We build test sets from your historical tickets, emails and records so accuracy is measured, not assumed.
GPT, Claude, Gemini or open models on your own cloud, chosen per task for cost, latency and quality.
Dashboards for runs, tool calls, failures and cost so you always know what your agents are doing.
We start with the single highest-value task, prove it with your data and your team in the loop, then expand the agent’s autonomy step by step.
We pick the model and orchestration stack per use case and connect it to the systems your agents need to act in.
A proven process to turn your ideas into powerful digital solutions.
We pick one task, write its success criteria and collect real examples to test against.
Tools, memory, prompts, guardrails and the hand-off path are designed and reviewed with your team.
We build, run it against hundreds of real cases and tune until accuracy meets the bar.
Shadow mode, then supervised, then autonomous, with monitoring and regular reviews.
Answers to the questions we hear most often. Need more detail? Talk to our team.
A chatbot answers questions. An agent can plan, call tools such as your CRM or order system, take actions and check its own results, so it completes tasks rather than only replying.
Every agent has an explicit list of allowed actions, confidence thresholds and approval steps. Risky actions such as refunds or outbound emails can require a human to confirm before they run.
Yes. We connect agents to any system with an API, and build connectors for legacy tools, databases and spreadsheets where no API exists.
It depends on the task. We often combine a strong model for reasoning with a cheaper model for routine steps, and we can run open models inside your own cloud where data residency matters.
A focused single-task agent typically goes live in four to six weeks, including evaluation on your real data and a supervised rollout period.
Tell us the task that eats the most hours and we’ll come back with an agent design, evaluation plan and a fixed-price estimate.
Or schedule a free consultation
AI · Software · Digital Commerce
info@indexiz.com
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