AI Agents and Automation

Multi-step agents with tools, logging, and human review — so repetitive work moves forward without losing control of quality or cost.

AI agents
and automation we offer

We design agents that call tools, follow policies, and escalate — not free-running scripts that surprise ops.

01
Multi-step agents
Plan, act, and verify across tools with clear stop conditions and retries.
02
Workflow automation
Ticket triage, enrichment, scheduling, and follow-ups that cut copy-paste work.
03
Human review gates
Approvals before irreversible actions — refunds, sends, or customer-facing replies.
04
Observability
Traces of every tool call and decision so you can debug and improve the agent.

Describe the workflow, the tools involved, and where humans must stay in the loop — we will propose a scoped pilot.

Pick the capabilities your product needs — we wire them in when the business case is clear.

01
Tool-using agents
Search, CRM updates, tickets, and custom APIs behind permissioned tool schemas.
02
Policy and prompts
Brand voice, allowed actions, and refusal rules encoded where the agent decides.
03
Retry and recovery
Idempotent steps and backoff so flaky APIs do not leave half-finished work.
04
Action allowlists
Only the tools and destinations you approve — nothing open-ended by default.
05
Run analytics
Success rate, cost per run, and time saved so automation has a business case.
06
Channel triggers
Start agents from email, chat, forms, or schedules without a new control plane for every team.
07
Custom tools
Wrap internal services so agents can do real work in your domain.
08
Operator consoles
Queues for review, override, and feedback that improve the next run.
Want agents that finish work — and leave an audit trail?
Discuss AI agents

They successfully developed our mobile apps and we were pleased. Understanding, collaborative, and their project management was effective throughout.

C&CEO & FounderSadapay

We start with one high-volume workflow, add tools carefully, and only expand after runs are measured and stable.

01
Discovery
Pick the workflow, define success, and list tools plus actions that are off-limits.
02
Design
Map steps, review gates, and evaluation cases for the first agent.
03
Development
Implement tools, prompts, and logging in Agile slices with a staging sandbox.
04
Testing
Replay cases, failure drills, and supervised pilots before full traffic.
05
Support
Watch runs, tune policies, and add tools as the agent earns trust.

Languages, platforms, and cloud tools we use to design, evaluate, and ship AI products.

1
Control over autonomy
Agents expand only as far as your policy allows — with humans on critical actions.
2
Tool discipline
Small, typed tools beat sprawling plugins that are hard to secure or debug.
3
Full run traces
Every decision and API call is inspectable when something goes wrong.
4
Cost visibility
Token and tool spend tracked per workflow so automation stays economical.
5
Pilot-first delivery
One workflow proven before we multiply agents across the organization.
6
Steady improvement
Feedback from operators feeds prompt and tool updates after launch.