Agentic AI systems
Software that does the work, not just the ticket.
We design and ship agents wired directly into your systems — with the evaluation, guardrails, and observability production actually demands, not a demo.
Ask Logos AI about this →What this covers
Separate, specialized agents for distinct jobs — onboarding, planning, analysis — wired together, rather than one general-purpose bot trying to do everything at once.
Agents wired directly into your own systems and data, often through an MCP layer, so they act on real information instead of a static knowledge base.
The testing and monitoring layer that keeps an agent reliable in production — eval sets, guardrails, and observability, not just a demo that worked once.
Agents that know when to hand off to a person — for approvals, edge cases, or anything outside their confidence — instead of operating as an unsupervised black box.
For teams ready to move past a chatbot pilot into agents that own real outcomes.
AI doubt solver
Answers student doubts instantly with RAG over a huge question bank.
AI Mentor
A multi-agent personal mentor that handles onboarding, weekly planning, test analysis, and learning-path generation — wired directly into the client's own student data and content library.
Multi-channel lead nurturing engine
Agent-run outreach across phone and WhatsApp that reads each lead's score and disposition, then hands off cleanly between channels instead of restarting the conversation.
Psychometric assessment platform
A full-stack assessment platform with an AI virtual mentor built in.
DGR Bot
Multi-agent Q&A over live SCADA data — generation and asset health, on demand.
Health Companion
A multi-agent system over a medical knowledge graph, running both lead gen and support.
AI Data Analysis Assistant
An agentic assistant that queries the client's data warehouse directly through MCP.
Frequently asked questions
The same answers our chat gives — no need to open it just to check.
How is an agent different from a chatbot?
A chatbot answers questions. An agent takes actions — looking something up, calling an API, updating a record, escalating to a person — chained across steps toward an outcome, not just a single reply.
What happens when the agent gets it wrong?
Every agent we ship has evaluation and guardrails built in, not bolted on after — bounded actions, confidence thresholds, and human-in-the-loop checkpoints for anything consequential. We'd rather it say "not sure" and escalate than guess.
Can it connect to our existing systems?
Agents are only useful wired into what you actually use — CRM, internal APIs, ticketing, databases. Honestly, that integration work is most of the build, more than the model itself.
Is there human oversight of the agent?
In practice: the agent handles the routine path end-to-end, and routes anything ambiguous, high-stakes, or unfamiliar to a person before acting. You decide where that line sits based on risk.
How do you measure if it's working?
We define success metrics with you before launch — resolution rate, accuracy against a held-out test set, time saved, escalation rate — and instrument the agent to report them from day one.
Which AI model do you use?
Whichever fits the task and your constraints — we're not tied to one model provider. Some agents run on multiple models across different steps of the same workflow.
What's included?
We design and ship agents wired directly into your systems — with the evaluation, guardrails, and observability production actually demands, not a demo. Concretely, that covers: multi-agent system design, tool- and api-integrated agents, evaluation & guardrail frameworks, human-in-the-loop workflows.
Can I see proof of work?
Here's real work we've shipped under agentic ai systems:
See the work above ↑How do you actually work, day to day?
We work in small, hands-on pods paired with AI tooling at every stage — spec, code, review, test. Practitioners, not a bench, AI-paired by default, Model- and stack-agnostic, Built to transfer.
How much does this cost?
Pricing depends on scope, so we don't quote a shelf rate here — a short conversation gets you an actual number, usually within a week of scoping.
How long does an engagement take?
Most engagements are scoped within a week of an initial conversation, with the pod starting shortly after.
What makes you different from other AI agencies?
The short version: practitioners who actually ship, not a bench of trainees; AI-paired by default rather than as a pitch; no lock-in to a specific model or cloud; and we build things your team can actually own afterward.