AI agents
An AI agent completes work instead of just discussing it: it reads the input, decides the next step, calls the systems it’s allowed to touch, and produces a finished output — a filed record, a drafted reply, a flagged exception.
For agencies whose clients are asking for AI that does the work — processing, triage, research — and need it in production, under your brand.
- Fixed-price / build
- $3,000–$8,000
- Pilot to proof
- 2 weeks
- Defect warranty
- 90 days
Why an agent has to be engineered.
What separates an agent commercially is permissions: it can look things up, write records, and move work forward — which is exactly why it has to be engineered rather than prompted. Every capability an agent has is a capability it can use wrong.
A production agent is mostly boundaries: what it may read, what it may write, and when it must stop and hand the work to a person. We scope those boundaries in writing the same way we scope features — the refusal behavior and the escalation path are line items in the spec, not afterthoughts.
Agents are grounded in your client’s real content and systems — retrieval over approved sources, tools with scoped credentials — not fine-tuned mystery models. Grounding keeps the output auditable: you can always ask where a claim came from.
If the deliverable is answers in a conversation rather than completed work, you’re scoping a chatbot. Read about AI chatbots.
When an agent is the right build.
Document-heavy operations
Contracts, invoices, applications, claims — inbound paper that a person currently reads, retypes, and routes. An agent extracts, files, and flags the exceptions, so the person handles only the exceptions.
Triage and routing
Support queues, lead inboxes, intake forms: work whose first hour is classification. An agent reads, categorizes, drafts the first response, and routes — with the send button left human wherever the stakes say so.
Research and enrichment
Gathering firmographics on a lead list, checking a fact across sources, assembling a brief. Work that is real but never urgent enough to staff — which is why it doesn’t get done.
The ceiling of a workflow
A rule-based automation that keeps hitting cases rules can’t express. An agent step inside the workflow handles the unstructured middle; the workflow keeps the deterministic ends.
Example agent builds.
Illustrative examples — the shape of work this line covers, not client case studies. Builds are quoted fixed-price from the published range ($3,000–$8,000 / build) before work starts.
Document-processing agent
Reads inbound contracts or invoices from a shared inbox, extracts the commercial terms into the client’s system of record, and files anything ambiguous into a review queue with its reasoning attached.
Support triage agent
Classifies inbound tickets, drafts a grounded reply for human approval, and escalates the cases it was told never to answer alone.
Research agent
Takes a list of target accounts, gathers public firmographics, and returns a one-line qualification note per account — sourced, so a person can check any claim in one click.
How we build agents.
Agent work is specified by behavior. Alongside features, the signed spec includes a set of pass/fail examples — real inputs and the outputs they must produce or refuse. QA runs against those examples before you see the build, and the 90-day warranty is measured against the same spec.
Defaults are conservative: human approval gates sit anywhere output leaves the building, every action the agent takes is logged, and credentials are scoped to the minimum the job needs and revoked at handover — the same least-privilege rules as everything else we ship.
The mechanics are the same on every line we ship:
- 01Pilot first — Every relationship starts with one real project: $1,000 flat, two weeks, fully credited toward month one of any retainer.
- 02Scoped in writing — Scope, milestones, and — on fixed-price work — the price, signed before work starts. The spec is the contract QA runs against.
- 03One point of contact — Javid scopes every project and answers inside four business hours; every active engagement gets a written status each Friday.
- 04Founder QA — Every deliverable is checked against the signed spec before you see it — behavior, edge cases, and security.
- 05White-label handover — Repos, credentials, and docs transfer to accounts you or your client control. Nothing we ship carries our name.
- 0690-day warranty — If a delivered build doesn’t match its signed spec, we fix it free for 90 days after handover.
Technologies
Defaults, not dogma — where your client already has a stack, we build in it.
- OpenAIModels
- AnthropicModels
- LangGraphAgent orchestration
- MCPTool connections
- n8nSurrounding workflow
- SupabaseState & retrieval
Questions about AI agents.
How do you keep an agent from doing something it shouldn’t?
By construction, not by prompt. The agent gets scoped credentials rather than broad access, allowed and forbidden actions written into the spec, approval gates on consequential steps, and a full action log. If a step can’t be made safe, it stays human.
How do you QA something non-deterministic?
With a fixed evaluation set written into the spec: inputs the agent must handle and inputs it must refuse. Model outputs vary; the pass/fail behavior doesn’t get to. That evaluation set is also what makes the defect warranty meaningful on an AI build.
What does the client see?
Whatever you put your name on. The agent runs in accounts the client controls, carries your brand or none, and nothing in the deliverable mentions us — the same white-label terms as every build.
Related service lines.
AI chatbots
Assistants grounded in your client’s real content — support, internal knowledge, lead capture — with refusal scope and human handoff built in.
Workflow automation
Multi-step business processes — intake, enrichment, reporting, back-office ops — built to run without a person pushing them.
API integrations
Custom connections between the systems your clients already pay for — kept in sync with auth handling, retries, and idempotency.
Start with one real build.
Scope your first project as the pilot — $1,000 flat, two weeks, fully credited toward month one of any retainer. If the work isn’t retainer-quality, you keep the deliverable and walk.