AI Agent Development Services
Custom AI agents that take real work off your team, built and deployed by engineers.
Who this is for
If any of this sounds like you, we should talk.
You have a process an agent could run end to end
Lead triage, research, report drafting, ticket routing, data entry. The steps are known, the volume is real, and a person is still doing all of it by hand.
You tried a ChatGPT wrapper and hit the ceiling
A prompt in a chat window is not an agent. You need tool use, memory, structured outputs, and guardrails, and that takes real engineering, not another subscription.
Your team is buried in repetitive knowledge work
The same lookups, the same summaries, the same copy-paste between systems, every day. That work is exactly what a well-scoped agent should absorb.
You are a SaaS or agency adding agent features
Your roadmap says agents, your team is at capacity. You want a build partner who ships production agent features on spec and hands over clean code.
What changes for you
Outcomes you can point to, not features you can ignore.
- An agent that completes a defined job (triage, research, drafting, routing) without a human driving every step.
- Tool and API integrations so the agent acts in your real systems, not just a chat window.
- Guardrails, logging, and human approval gates wherever a wrong action would be expensive.
- An evaluation suite that measures agent accuracy before launch and catches regressions after.
- Documented code you own, with no lock-in to a wrapper platform.
What is included
Scope, organized by phase.
Discovery (Phase 1 of 3)
Phase 1
Discovery
What we lock down in this phase before moving on.
- Use case selection and feasibility check
- Data, tool, and API inventory
- Success metrics and failure cost analysis
- Human-in-the-loop boundaries
How an engagement works
From hello to handoff, step by step.
Scoping call
We walk through the process you want automated, the systems involved, and what a wrong action would cost. You get an honest feasibility read.
Scoped proposal in 48 hours
A written scope with the agent's job definition, integrations, success metrics, and milestones. Fixed deliverables, no vague hourly traps.
Working prototype first
We build a narrow version of the agent against real sample data early, so you see it act before we harden anything.
Harden and integrate
Evaluation suite, guardrails, approval gates, and the production integrations. The agent earns trust one verified behavior at a time.
Deploy and monitor
Production launch with logging, alerting, and a review cadence. You see what the agent did, why, and where it deferred to a human.
Case study
WitsCode AI Visibility Checker
A production AI tool live on our own site, running the full query, evaluate, score, and report loop without a human in it, and feeding qualified leads into our pipeline. We ship for clients the same way we ship for ourselves.
Businesses could not see whether AI assistants like ChatGPT, Perplexity, and Google AI Overviews mention them at all. Checking by hand means running dozens of buyer-style prompts and reading every answer, so almost nobody does it.
We built our own multi-step AI pipeline: it takes a domain, generates the questions a real buyer would ask, runs them against AI answer engines, parses and scores each response for brand presence, and returns a visibility report, with lead capture wired straight into our CRM.
Why us
What you get with WitsCode that you don't get elsewhere.
We run agents in our own business
Our AI Visibility Checker and our n8n lead pipeline run our own operations daily. You get patterns proven in production, not a first experiment on your budget.
Engineers, not prompt hobbyists
Since 2019 we have shipped 300+ websites and applications. Agents get the same discipline: typed code, tests, evals, and deployment pipelines.
You own everything
No wrapper platform, no per-seat middleman, no lock-in. The agent is code in your repository, documented so any engineer can extend it.
WitsCode rebuilt our Shopify store so it finally converts the traffic we were already getting. They understand speed and storytelling in equal measure, and the store has been a real growth lever since launch.
Frequently asked
Questions before you reach out.
An AI agent development company builds software that uses a large language model to complete multi-step work autonomously: reading inputs, deciding what to do, calling tools and APIs, and producing a finished output. That includes the model orchestration, the integrations with your systems, the guardrails, and the monitoring. The deliverable is a working system, not a prompt document.
A chatbot answers questions in a conversation and stops there. An AI agent takes actions: it can search your data, call APIs, update your CRM, draft and send documents, and chain multiple steps toward a goal with limited supervision. Chatbots inform. Agents do work. Most business value sits on the agent side.
With layered controls: structured outputs that constrain what the agent can do, permission scoping so it only touches approved systems, human approval gates on high-cost actions, full logging of every step, and an evaluation suite run before and after every change. High-risk actions stay behind a human until the accuracy data says otherwise.
Whichever model fits the job after we test against your actual tasks. We build model-agnostic, so the orchestration layer can switch between providers such as Anthropic, OpenAI, and Google as quality and cost profiles change. You are never welded to one vendor, and model choice is documented with the reasoning.
A focused single-job agent typically reaches a working prototype in the first weeks, with hardening, integrations, and evaluation bringing most builds to production in 4 to 8 weeks. Scope drives the timeline: number of integrations, risk level of the actions, and how much evaluation the failure cost demands. You get a firm timeline in your proposal.
No, but you need accessible data. Agents work with the systems and documents you already have, and part of discovery is mapping what the agent can reach and what state it is in. If data quality genuinely blocks the use case, we tell you before the build starts, not after.
Ready to put an agent on real work?
Book a scoping call. You get an honest feasibility read and a scoped proposal within 48 hours.