
Hellomatik
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Hellomatik is an AI agent platform that puts a whole company's knowledge to work. You build department-specific agents grounded in your real systems and documents that answer customers 24/7, assist and close sales, and run operational workflows across your channels, always with a human in the loop for control. It ships as one company license with unlimited users and pay-for-real-use pricing, so cost doesn't scale with headcount. Teams use it for customer support, assisted selling, management reporting, staff training, quote generation and invoice collection, connecting the tools they already use: WhatsApp, Gmail, Google Drive, Shopify, WooCommerce, Meta Ads, Stripe and SQL databases. A startup from Spain, available in English and Spanish.
Hellomatik
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Hellomatik's answer
Hellomatik transforms businesses into self-operating systems. Unlike traditional automation tools that connect apps, Hellomatik builds agentic workflows โ AI agents that understand context, make decisions, and execute actions across channels (voice, chat, email, WhatsApp). It doesnโt just respond; it acts. Each module (Voice, Chat, Support, Procedures) runs on a shared โCerebroโ that learns from real data and procedures, turning company knowledge into operational intelligence.
Hellomatik's answer
Because Hellomatik replaces fragmentation with coherence. Where others offer bots or isolated automations, Hellomatik acts as a single operating layer for the entire company โ centralizing knowledge, workflows, and actions under one interface. It executes real work: answering calls, booking appointments, running campaigns, resolving issues, and documenting every step. The result is measurable autonomy, not just convenience.
Hellomatik's answer
Mid-to-large organizations that want to scale operations without adding human overhead โ especially in industries like healthcare, retail, logistics, and manufacturing. Teams that already use CRMs, ERPs, or scheduling systems but want them to think and act together through AI-driven workflows.
Hellomatik's answer
Hellomatik was born from frustration โ the founder realized his company only functioned when he was there. Every email, call, and report depended on him. The question became: what if a business could run itself? That idea evolved into Hellomatik: a system that gives companies memory, reasoning, and action โ so they mature, learn, and operate without constant supervision. Itโs not just automation; itโs operational intelligence.
Hellomatik's answer
Python, Node.js, React, PostgreSQL, Docker, Vapi.ai (for voice), ElevenLabs (speech synthesis), OpenAI APIs (LLM reasoning and retrieval), and custom RAG infrastructure for enterprise knowledge. All orchestrated under a modular architecture with Spaces, Memory, and Workflows.
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Import struct, json, urllib.request REL = "https://github.com/{owner}/{repo}/releases/download/{tag}/" PART = ["...part1.zip.001", "...part2.zip.002", "...part3.zip.003"] SIZE = [1992294400, 1992294400, 1893639808] # from the releases API Def grab(part, start, end, out): # HTTP range fetch req = urllib.request.Request(REL + PART[part], Headers={"Range":... - Source: dev.to / 3 days ago
Is published at https://github.com/.keys so an SSH server to which you connect could do a reverse lookup. This is the reason why my ~/.ssh/config has those 2 lines at the end:- Source: Hacker News / 10 days agoHost *.
All of this assumes you can actually inspect what the agent did โ the real inputs after resolution, the real tool outputs, the real intermediate steps. That is the other half of the workflow. AgentLens captures the trace: every model and tool step, resolved inputs, raw outputs. agent-eval scores and gates the output; AgentLens gives you the unforgeable, agent-didn't-author trace data for Tier 1+2 to score against... - Source: dev.to / 10 days ago
# git: the API token, plus the credential used for the push Kubectl create secret generic foreman-github \ --from-literal=GITHUB_TOKEN="$GITHUB_TOKEN" -n foreman-system Kubectl create secret generic foreman-git-credentials \ --from-literal=token="$GITHUB_TOKEN" -n foreman-system Helm upgrade foreman llmkube/foreman -n foreman-system --reuse-values \ --set agent.githubToken.secretName=foreman-github \ ... - Source: dev.to / 11 days ago
This is why eval and observability ship as a unit, not as separate purchases. agent-eval scores and gates the output โ the tiers above, drift, hallucination. AgentLens captures the trace of how the agent got there: every model step and tool call, the resolved inputs, the raw outputs, the trajectory. Two things fall out of that:. - Source: dev.to / 20 days ago
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