Custom AI agents that actually ship.

A chatbot follows scripted conversation flows and returns text. An AI agent reasons about goals, accesses tools and data, and takes autonomous actions across your systems.

A chatbot answers "what's your refund policy?" An agent reads the customer's order, checks eligibility against your policy, calls Stripe to issue the refund, updates the CRM, and sends the confirmation email — without anyone touching it. Different category of software entirely.

For tool-calling agents, Claude consistently outperforms GPT-4o on accuracy, instruction-following, and reasoning over long contexts — which is the entire game for production agents. We use GPT-4o, Llama, and Mistral when a task specifically benefits from them, but Claude is the default because it's the most reliable in production.

This is one of the topics we'll cover in our launch Playbook posts.

A single-purpose agent (Tier 01 Sprint) ships in 4 weeks from kickoff. Multi-agent systems (Tier 02 System) take 8–12 weeks. Embedded partnerships (Tier 03) ship multiple agents over 6–12 months.

You see a working prototype within 10 business days of kickoff on every engagement. No "here's a slide deck, real progress in month 3" theatre.

This is the right question to ask — and most agencies don't have a real answer. We do.

Every agent ships with: (1) confidence thresholds that pause execution and request human approval before high-impact actions, (2) output validation against your business rules before any action commits, (3) rollback paths for reversible operations, and (4) full audit logging of every action with the data the agent saw.

When errors do occur, they're flagged immediately and fed back into the agent's eval suite so they don't recur. For high-stakes workflows we ship human-in-the-loop checkpoints by default.

Always yours. Never ours. We deploy to your AWS, GCP, Azure, or self-hosted environment. You own the code repository, the deployment pipeline, the data, and the API keys. We get scoped access for development and ongoing operations only.

If you want to part ways, you keep everything. No vendor lock-in. No "but the agent only runs on our platform" gotchas.

Use them for what they're good at: ad-hoc research, content drafting, simple Q&A from a single document. They're excellent at those tasks.

They break down when you need an agent that accesses your internal systems, executes multi-step workflows, maintains state across sessions, or coordinates with other agents. They lack audit logging, role-based permissions, output validation, and compliance guardrails — the four things that separate a demo from production.

If a no-code tool can solve your problem, use it and save the money. We only take engagements where custom agents are clearly the right answer.

Yes — integration is the entire point. We've built agents that connect to Salesforce, HubSpot, Zendesk, Intercom, Slack, Microsoft Teams, Stripe, Notion, Linear, Jira, custom REST and GraphQL APIs, and Postgres / MongoDB / Snowflake databases. If it has an API, the agent can use it.

For databases without good APIs, we usually deploy a thin wrapper layer first so the agent has a clean, scoped contract to work against.

The default architecture is self-hosted on your infrastructure, which solves the bulk of compliance concerns by keeping your data inside your perimeter. On top of that we ship: role-based access controls, encryption at rest and in transit, audit logs of every agent action, and content guardrails to prevent sensitive data exposure.

For regulated industries (healthcare, finance, legal) we work with your compliance team upfront — GDPR, HIPAA-aligned workflows, SOC2 controls. We're not yet ISO-certified ourselves; if that matters to your procurement team, mention it on the scoping call.

Bini is currently a founder-led studio operating out of Dhaka, Bangladesh, with select contractors brought in for specific engagements. Honest about that because it matters: you get senior-level work directly from the founder, not handed off to a junior the moment the contract is signed.

We're async-first. Daily progress updates via Slack or Linear. We work while your team sleeps and ship while you wake up. For most clients in US/EU/AU time zones, this is actually a feature.

That's what the 30-min scoping call is for. Bring us your most painful, repetitive workflow — we'll diagnose whether an agent is the right answer, what shape it should take, and what it would cost. No charge, no slides, no obligation.

About 40% of those calls end with us recommending you don't build a custom agent at all. We'd rather decline a bad-fit project than ship something that won't deliver value.

Monthly: review agent performance metrics, tune prompts based on real interaction data, handle model upgrades when providers ship new versions, expand tool integrations as your workflows evolve. You get a written report each month with: tasks handled, accuracy trends, token cost, and recommended changes.

Maintenance starts at $300/mo for a single Sprint agent and scales with the number and complexity of agents in production. For a System tier engagement with 3 agents, expect $800–2,500/mo.

Generally no. We're builders, not consultants — strategy detached from execution rarely produces real systems. The exception: a half-day paid architecture review ($1,500) where we audit your existing AI deployment or proposed architecture and give you a written assessment with recommendations.

If you don't have a clear build need yet, the free 30-min scoping call usually surfaces enough to decide.