AI Agent Development Company
Custom AI agents that automate the workflows your margins depend on.
Zantise is an AI agent development company for enterprises that need agents in production, not in slide decks. We design, build, and operate custom AI agents that read your systems, make decisions inside defined guardrails, and complete work that used to queue on a human desk.
Every agent ships with the parts most vendors skip: evaluation suites, audit logs, rollback paths, and a clear answer to “who maintains this after launch.” Your data stays in your boundary and never trains third-party models.
- typical first agent in production
- 6–9 wks
- typical first agent in production
- of agents shipped with eval suites and audit logs
- 100%
- of agents shipped with eval suites and audit logs
- client data used to train third-party models
- 0
- client data used to train third-party models
What we build
Where this engagement earns its keep.
Operations agents
Agents that triage tickets, reconcile invoices, process claims, and chase exceptions across ERP, CRM, and ITSM systems — with human approval gates where the cost of error is real.
Knowledge agents
Retrieval-grounded agents over your contracts, policies, and institutional knowledge. Answers carry citations back to source documents, so your team can verify instead of trust.
Customer-facing agents
Support and onboarding agents that resolve — not deflect. Tone-controlled, escalation-aware, and measured on resolution rate and CSAT, not conversation count.
Agent evaluation & hardening
Already built an agent that works in demos and fails in the wild? We add eval harnesses, regression suites, guardrails, and observability so it survives real traffic.
Common questions
Asked by every buyer who's been burned before.
How long does it take to build a custom AI agent?
A scoped production agent typically takes six to nine weeks: two weeks of discovery and data access, three to five weeks of build and evaluation, and a controlled rollout with human oversight before autonomy widens.
Which models and frameworks do you build on?
We're model-agnostic and pick per use case — Claude, GPT, Gemini, or open-weight models in your VPC when data can't leave your boundary. Orchestration runs on our Meridian platform or your existing stack.
How do you keep an AI agent from making costly mistakes?
Guardrails are designed before the agent is: permission scopes, spending and action limits, approval gates for irreversible steps, full audit trails, and evaluation suites that run on every change — the same discipline you'd demand of a new hire.
Who maintains the agent after launch?
Either your team — we hand over runbooks, evals, and training — or ours, under a managed operations agreement with response-time SLAs and monthly performance reviews.
Tell us what should stop being manual.
A 30-minute scoping call with an engineer — you'll leave with a candid read on feasibility, cost, and whether AI is even the right answer.