AI Agents That Do Real Back-Office Work — An AI Co-Worker, Not a Chatbot.
We build custom AI agents that read documents, triage and route requests, draft responses, and update records inside your existing systems — then hand off to a human when unsure. Every agent ships with human-in-the-loop approvals, guardrails, and an audit trail — production-ready, not a demo.
Trusted by Teams Who Need AI to Actually Work
Sound Familiar?
Your team is drowning in repetitive admin — reading, sorting, copying, routing.
Inboxes, forms, PDFs, tickets. Skilled people spend half their week on work that follows a pattern but is too messy for a rigid script. It’s the perfect job for an AI co-worker — and the wrong job for another full-time hire.
Your chatbot pilot impressed everyone in the demo — and never reached production.
It answered scripted questions on stage, then fell over on real inputs, couldn’t touch your actual systems, and nobody trusted it enough to let it act. A demo is not a deployment. Production is a different discipline.
You're afraid of an agent that hallucinates or acts without oversight.
The nightmare isn’t a wrong answer — it’s an AI that confidently approves, sends, or updates the wrong thing with no one watching. Without human-in-the-loop checkpoints and an audit trail, u0022autonomousu0022 is a liability, not a feature.
Your automation can't read the messy stuff — emails, scanned contracts, free-text notes.
Traditional automation needs clean, structured input. Real business runs on unstructured documents and human language. When the input isn’t a tidy row in a table, rules-based tools stall — and a person has to step back in.
The tools you'd want to automate don't talk to each other — or to anything new.
Your ERP, CRM, ticketing, EHR, and shared drives each speak their own dialect. An agent that can’t reach into those systems is a clever toy. The hard part isn’t the model — it’s the integration.
You're worried it isn't safe or compliant to let AI act in a regulated workflow.
In healthcare and finance, u0022the AI did itu0022 is not an acceptable audit answer. You need to know exactly what the agent saw, what it decided, who approved it, and why — recorded and reviewable.
An AI Co-Worker, Not a Chatbot
A chatbot answers questions. An AI co-worker does the work: it reads the document, makes the judgment call, updates the record, and escalates to a human when it isn’t sure. The difference is production discipline — grounding in your real data, tight integration with your real systems, human approvals on anything that matters, and a full audit trail of every action. That’s the gap most u0022AI agentu0022 projects fall into. It’s the gap we build across.
AI Agent u0026 Automation Services
Custom AI Agent Development
For teams who need an agent that actually does something — not just chats.
We build agents with tool use (the agent can call your systems and APIs), memory and context, and human-in-the-loop checkpoints so a person approves anything consequential. Model-agnostic: we pick OpenAI, Anthropic, Gemini, or an open model based on the task, cost, and data-residency constraints — not a vendor allegiance.
- A scoped agent for a specific, high-ROI workflow — not a general u0022do anythingu0022 bot
- Tool/function-calling integration so the agent can read and act in your systems
- Human-in-the-loop approval steps and confidence thresholds for escalation
- Evals and a test harness so you can measure the agent before it goes live
Back-Office u0026 Admin Automation — the u0022AI Co-Workeru0022
For teams buried in operational admin.
This is the heart of what we build: an agent that reads incoming documents and requests, classifies and triages them, drafts the response or the record update, routes anything ambiguous to the right person, and only completes the routine, low-risk cases on its own.
- Document intake u0026 triage (emails, PDFs, forms, scanned files, free-text notes)
- Request routing — the right case to the right team, with a reason attached
- Draft-and-review workflows (the agent drafts, a human approves and sends)
- Record updates written back into your existing systems, with a full audit trail
AI Workflow Automation (Where RPA Stops)
For teams whose current automation breaks on judgment and messy input.
Classic RPA and rules engines are great at rigid, structured, repeatable steps — and useless the moment a case needs interpretation or an input arrives as unstructured text. We build the judgment layer: agents that handle the ambiguous cases, and hand the deterministic ones to the tools you already have.
- A map of which steps stay rules-based (RPA/scripts) and which need an agent
- Agentic handling of unstructured inputs and judgment calls
- Orchestration of multi-step workflows across systems and tools
- Fallbacks and human escalation for anything outside the agent's confidence
Agent Integration Into Your Existing Systems
For teams whose real challenge is connectivity, not the model.
An agent is only useful if it can reach your ERP, CRM, ticketing, EHR, and data — securely. We wire agents into the systems you already run, using your APIs, your auth, and your data-governance rules.
- Secure connectors to ERPs (e.g. Odoo), CRMs, ticketing, and internal APIs
- Retrieval over your own documents and data (RAG) so answers are grounded, not guessed
- Auth, permissioning, and data-residency handled to your standards
- Monitoring and retraining hooks so the agent stays accurate over time
How We Build Agents You Can Trust in Production
Scope the Task, Not the Fantasy
We start from one real, high-ROI workflow with a clear success metric. A narrow agent that reliably does one job beats a broad one that half-does ten. We define what u0022done rightu0022 looks like before we build.
Ground It in Your Data (RAG)
An agent that reasons from your actual documents, policies, and records — retrieved at query time — instead of a model’s general memory. Grounding is the single biggest lever against hallucination.
Give It the Right Tools u0026 Actions
Tool and function calling, plus Model Context Protocol (MCP), let the agent read and write in your real systems — through your APIs, with scoped permissions. The action layer is where integration engineering earns its keep.
Put a Human in the Loop
Anything consequential — an approval, a send, a record change — passes a human checkpoint or a confidence threshold. The agent proposes; a person disposes, until you’ve earned enough trust to widen its autonomy deliberately.
Guardrails u0026 Evals
Input validation, output constraints, and a standing eval suite that scores the agent against real cases on every change — so you catch regressions before your users do. We don’t ship an agent we can’t measure.
Audit Trail u0026 Monitoring
Every input the agent saw, every decision it made, every action it took, and who approved it — logged and reviewable. In regulated workflows this isn’t optional; it’s the whole point.
Industries We Serve
Healthcare Admin
u003cpu003eClinical and operational back-office work — intake documents, referrals, prior-auth paperwork, records updates — is drowning in repetitive, unstructured admin. An u0022admin co-workeru0022 that reads, triages, and drafts (with a clinician or coordinator approving) frees skilled staff for patient-facing work. Built to HIPAA/GDPR/KBV-grade auditability. See u003ca href=u0022/industries/clinical-ai/u0022u003eClinical AIu003c/au003e.u003c/pu003e
FinTech u0026 Finance Ops
u003cpu003eContract and document review, risk scoring, exceptions handling, reconciliations. Agents that read unstructured financial documents, apply explainable scoring, auto-complete the clean cases, and route the rest to an analyst — with the reasoning attached. This is exactly what we built for Eska.u003c/pu003e
Enterprise u0026 Customer Ops
u003cpu003eTicket triage and routing, response drafting, order and case updates across CRM and helpdesk. Agents that take the repetitive volume off your ops team and escalate the genuinely hard cases to a human, faster.u003c/pu003e
Education u0026 Internal Knowledge
u003cpu003eInternal knowledge assistants grounded in your own docs, policies, and handbooks — so staff get accurate, cited answers instead of digging through drives, and admin workflows (enrolment, support requests) get triaged automatically.u003c/pu003e
How We Engage
Scoping Call (30 min)
A Trembit AI engineer looks at where your team loses the most time to repetitive admin, and tells you honestly whether an agent is the right tool — and where it isn’t. No pitch deck, just a read on feasibility and ROI.
Pick One High-ROI Workflow (Pilot)
We choose a single, well-bounded workflow with a clear metric — volume handled, hours saved, turnaround time — and scope a pilot. Narrow and real beats broad and vague. You get a defined deliverable, not an open-ended research project.
Build With a Human in the Loop
We build the agent grounded in your data and integrated with your systems, with approval checkpoints from day one. It starts by proposing and drafting while humans approve — earning trust before it earns autonomy.
Measure, Harden u0026 Expand
We measure the pilot against its metric, harden the guardrails and evals, then widen the agent’s autonomy and scope deliberately — one proven workflow at a time. Most engagements grow from one agent into a suite.
Technology u0026 Expertise
We’re a software-engineering firm that builds and integrates agents into real systems — not a model lab and not a no-code-template shop.
LLMs (Model-Agnostic)
Agent Frameworks
Tool Use u0026 Actions
Retrieval (RAG)
Automation u0026 Orchestration
Integration
Engineering
Cloud u0026 Infrastructure
Automation Work We've Delivered
Real agents, in real business systems, with humans in the loop.
Automated Leasing Decision Pipeline
Eska FinTech
Challenge: An end-to-end agentic automation for a leasing business. The pipeline reads unstructured leasing contracts (Python NLP/OCR), scores credit risk with an explainable ML model, then auto-approves low-risk applications, routes high-risk ones to a human analyst with an AI risk breakdown attached, and flags borderline cases for review. It's wired into the client's Odoo ERP through a Node.js integration layer, with monitoring and retraining built in — human-in-the-loop back-office automation in production.
- Reads unstructured contracts via Python NLP/OCR
- Explainable ML risk scoring
- Auto-approve / route / flag with human-in-the-loop
- Wired into Odoo ERP; every decision traceable
Production Conversational Agent
AI-SkyTalk Aviation
Challenge: A real-time conversational AI agent built on Google Gemini (Multimodal Live API), with tool and context orchestration, validation rules to keep responses in-bounds, and n8n automation workflows behind it. Proof that we ship conversational agents with guardrails — not scripted demo bots — in a domain where wrong answers aren't acceptable.
- Real-time conversational agent on Gemini Multimodal Live
- Tool and context orchestration
- Validation-rule guardrails keep responses in-bounds
- n8n automation workflows behind it
What Our Clients Say
“The final solution substantially expedited our credit decision-making process, reducing it from four days to one. Working with Trembit was an excellent experience — their effective, on-time delivery and commitment to keeping us in the loop made our project a success.
“Their proactive team gets things done as if it were their own project, consistently delivering high-quality outputs. Trembit’s handy suggestions, adaptability, and customer-oriented approach stand out — but what really differentiates them is their ability to deeply understand business needs.
Why Choose Trembit to Build Your AI Agents?
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50+ Production projects delivered
We integrate into real systems — that's the hard part
u003cpu003eThe model is a commodity; making it read and act reliably inside your ERP, CRM, and EHR is not. Integration and reliability engineering is our core discipline, backed by 15+ years and 50+ production projects. See our u003ca href=u0022/services/system-integration/u0022u003esystem integrationu003c/au003e work.u003c/pu003e
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HITL By default, not bolted on
Human-in-the-loop reliability engineering
u003cpu003eWe don’t overclaim autonomy. We build agents that propose, draft, and escalate — with guardrails, evals, and approval checkpoints — and widen their autonomy only as they earn trust. That’s how an agent survives contact with production.u003c/pu003e
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KBV First certified in Germany
A compliance moat few AI shops have
u003cpu003eHIPAA, GDPR, and KBV experience — including the first KBV-certified psychotherapy video platform in Germany. When an agent acts in a regulated workflow, the audit trail and data-governance discipline are already how we work.u003c/pu003e
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Live Not a demo reel
A real production track record
u003cpu003eEska’s leasing decision pipeline and AI-SkyTalk’s conversational agent are live, integrated systems — not proof-of-concept notebooks. We build agents that run every day.u003c/pu003e