AI & Agents Automation, Orchestration & Integration
Five PoCs. Zero in production.
Most AI projects die in the gap between a working demo and a system real customers can rely on. We close that gap. Autonomous agents that plan, reason, use tools and execute, with evals, observability and cost controls baked in from day one.
and inside every PADISO product, including SearchFIT.ai, Capitaly.ai and D23.io. The problem
Sound familiar?
Every team trying to do AI properly hits the same five walls.
We have 5 AI PoCs in slides. Zero are in production. The CFO is asking why.
Our agents work in demos and fall over the moment a real customer touches them.
We shipped a chatbot. Customers hated it. We quietly turned it off and now nobody trusts AI projects internally.
Our LLM bill is up 4x in 6 months. Nobody can tell me what's driving it or which agent is the culprit.
Every team is building their own AI thing. No shared evals, no shared infra, no shared lessons.
What demo-grade AI actually costs you.
It isn't just the LLM bill. It's the trust hit, the team time, and the customer-visible failures that make every future AI project ten times harder to greenlight.
Engineering quarters lost to AI PoCs that never make it to a real user.
Higher LLM costs when there's no model routing, no caching and no per-feature attribution.
Of AI features quietly disabled within a quarter of launch when evals weren't there to catch regressions.
Bad customer-facing AI launch is enough to set the next AI project back two quarters.
The fix
Agents that survive contact with real users.
We don't ship demos. We ship agents that handle the boring 90% of cases without intervention, escalate the hard 10% to a human, and have a clean evaluation harness so you know when something regresses, before customers do.
Every build comes with the same backbone: model routing across Claude, GPT, Gemini and open-weight, RAG and tool use grounded in your actual data, evals and observability on every interaction, and cost controls so a bad prompt doesn't wake the CFO at 3am.
It's the same playbook we run inside every PADISO product, including SearchFIT.ai, Capitaly.ai and D23.io, and the same one we deploy at clients like Scentre Group, OOH and TFE Hotels.
What we build.
Six AI shapes we ship over and over again. Each one comes with evals, observability and a real plan for the day a model deprecates.
Agentic AI Workflows
Autonomous agents that plan multi-step tasks, use tools, call APIs and make decisions. Built on LangChain, CrewAI or hand-rolled where it earns its keep.
RAG Pipelines
Retrieval-augmented generation grounded in your knowledge base, contracts, tickets and product data. Hybrid search, reranking, citation-first answers.
Multi-Model Orchestration
Claude for analysis, GPT for generation, Gemini for multimodal, open-weight for cost. Smart routing through an AI gateway, not vendor lock-in.
Conversational AI
Customer-facing agents that understand context, hit your real systems, escalate cleanly to humans, and stay inside the brand and the policy.
Document Processing
Intelligent extraction from invoices, contracts, clinical notes and reports. Structured output that flows directly into your downstream systems.
Workflow Automation
Connect your tools with n8n, Zapier and Make plus custom code. AI-driven workflows that eliminate manual handoffs and keep your team out of inboxes.
The backbone every agent ships with.
The four things that turn a demo into a production system. Skip any of them and you're back in PoC purgatory.
Evals
Versioned test cases for every prompt, every tool call, every agent path. Regressions caught before deploy, not by customers in support tickets.
Observability
Per-trace token, latency, cost and outcome data. You know what every agent did, why, and what it spent doing it.
Cost controls
Per-feature, per-tenant and per-customer budgets. Caching, model fallback and rate limits so the LLM bill stays linear, not exponential.
Governance
PII handling, prompt injection defences, output filters, audit logs. Legal can sign off, customers can trust it, you can sleep.
Who this is for.
SaaS shipping AI inside the product
You need customer-facing AI features that actually work, with per-tenant evals, cost controls and a UI that makes the magic explainable. Not a chatbot bolted onto the corner of the screen.
Mid-market operators automating ops
Health, Hotel & Hospitality, Retail, Logistics. You want agents inside support, dispatch, scheduling, RCM and back-office workflows that handle the boring 90% so your team handles the rest.
CTOs cleaning up failed AI experiments
You inherited 5 PoCs from 3 vendors. Nothing's in production. Costs are climbing. We consolidate the platform, kill what isn't earning, and ship the two or three things that actually move metrics.
Stop shipping demos. Start shipping agents.
Book a 30-minute call. We'll tell you which of your AI ideas is closest to production-ready and what 90 days of focused build would unlock.