Production agents that ship and ship again
AI Agent Development
Autonomous agents that do real work inside your stack: read your systems, take scoped actions, escalate when confidence drops, and log every decision for audit.
What this is
Most agent projects die at the demo. They work on a laptop with a friendly prompt and a clean input, then fall apart the first time a customer sends a screenshot, a half finished sentence, or a request that touches billing. We build agents the way we build any other production service: scoped permissions, typed tool contracts, retries with backoff, structured logging, evaluation gates before each release, and a rollback path that a non engineer can trigger.
What is included
- Tool calling agents wired into your CRM, helpdesk, database, and internal APIs
- Multi step planning with hard budget ceilings on tokens, time, and spend
- Human in the loop approval gates on any action that moves money or data
- Evaluation harness with golden datasets so a model swap never silently regresses
- Full observability: traces, token cost per run, failure taxonomy, alerting
How we run it
Scope the risky part
We identify the single hardest judgement in the workflow and prototype that first. If the agent cannot do that reliably, nothing else matters.
Build the tool layer
Typed tools with validation, idempotency keys, and least privilege credentials. The agent only reaches what it needs.
Wire evals
Golden cases from your real history, scored automatically. No release ships without passing the gate.
Ship behind a gate
Shadow mode first, then human approval, then narrow autonomy on the cases the data says are safe.
Operate and widen
Weekly review of failures, expanded autonomy where evidence supports it, tightened rails where it does not.
What you receive
- Agent service deployed to your infrastructure or ours
- Tool layer with typed schemas and input validation
- Eval suite plus a regression gate wired into CI
- Operator console for approvals, replays, and manual overrides
- Runbook covering failure modes, escalation, and rollback
- Typical duration4 to 8 weeks
- Indicative investmentFrom $8,500
- CategoryAutomate
- Starts withFree written quote
Opens the quote form with AI Agent Development already selected.
Third party names and logos are shown for identification only and do not imply affiliation or endorsement.
Month one is refundable. If the first month does not land we return it. We would rather refund than carry a project neither side believes in.
The return
What this gives back, every month
Ranges, not promises. They come from published 2026 automation benchmarks and our own delivery data, and the audit re-runs them against your actual volumes before you commit anything.
Why buy it
The case for doing this now
You are already paying for this work
The hours do not disappear when you ignore them. A team of six spending two hours a day each on triage and data entry is carrying roughly $57,000 a year in salary against work no human enjoys.
Volume grows faster than headcount
Ticket and lead volume scales with revenue. Headcount scales with hiring cycles and budget approval. An agent absorbs the gap without a job posting.
The alternative costs forty times more
A fully loaded senior AI engineer in the US runs $300,000 to $460,000 a year. This engagement is a single build fee, and you own the code afterwards.
Compared to the alternatives
What the same outcome costs elsewhere
Every option below solves some version of this problem. Here is what each one actually costs over twelve months.
| Your options | Upfront | Ongoing | Time to value | What you get |
|---|---|---|---|---|
| Do nothing | None | $4,750/mo in staff time | Never | The work continues, the cost compounds |
| Hire an AI engineer | Recruiter fee | $25,000 to $38,000/mo | 4 to 6 months | Fully loaded US cost, plus hiring risk |
| Typical AI agency | $20,000 to $50,000 | Retainer on top | 8 to 16 weeks | Often subcontracted after the sales call |
| deepaibots | $8,500 | Optional from $1,200/mo | 4 to 8 weeks | Named senior engineer, source transfers to you |
What changed
Why this is worth buying in 2026 and was not in 2024
The scope of this service moved with the tooling. These are the shifts that make the engagement materially better than the same brief eighteen months ago.
- 01
Native tool calling is now reliable enough for production. Two years ago agents needed brittle output parsing; today the model returns typed structured calls your code validates directly.
- 02
Inference cost per million tokens has fallen far enough that per-run economics work at SMB volume, not just enterprise scale.
- 03
Evaluation harnesses became standard practice. A model swap is now a config change plus a scored regression run rather than a rebuild and a leap of faith.
FAQ
AI Agent Development: your questions
How autonomous will the agent be on day one?
Not very, deliberately. We launch in shadow mode where the agent drafts and a human approves. Autonomy expands per case type once the eval data supports it, usually within four to six weeks.
What if a model gets deprecated?
The tool layer and evals are model agnostic. Swapping providers is a config change plus a full eval run, typically under a day.
Who owns the code?
You do. Full source, infrastructure as code, and documentation transfer on final invoice.
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Get a fixed price for ai agent development
The quote gives you a written scope and a fixed price. No obligation to proceed.