Everything Worth Asking.

Orbit Dashboard is a self-serve SaaS. You log in, add a pre-built AI system from the marketplace, connect your own accounts, and run it from one dashboard. We build, host, and maintain every system; you configure it and watch it work. Lead generation, outbound that does not read as AI, support agents customers do not hate, and content that sounds like you.

A self-serve SaaS. You subscribe to pre-built systems, connect your own accounts, and run them yourself from one dashboard, month to month. We build and host every system so you never touch the code. Need something fully bespoke? That lives in our Enterprise plan.

Senior engineers with backgrounds in distributed systems, data engineering, and applied AI. We use AI to accelerate the boring parts of development, but architecture, prompts, evals, and the on-call schedule are owned by humans. Every system goes through review and integration testing before it touches production.

A single web app where you run every Orbit system from one place. Status, KPIs, controls, audit logs, and approvals all live there. We host it, monitor it, and update it. You log in.

Regular automations follow rigid rules: if X, do Y. Agentic systems use AI to think, decide, and adapt. They handle nuance, chain multi-step actions, and improve as inputs change. Think of it as the difference between a vending machine and a junior employee who gets better every week.

Automation runs the same playbook every time. AI looks at the inputs and chooses the playbook (or writes a new one). Most real systems we ship are a mix: deterministic plumbing for the parts that should never vary, AI for the parts that need judgment.

A coordinator AI delegates pieces of a job to specialist sub-agents (a researcher, a writer, a critic, a reviewer). It helps when work is genuinely separable and benefits from focused prompts or isolated context. We use multi-agent for research-heavy and review-heavy tasks. We do not use it because it sounds futuristic. One sharp agent beats five mediocre ones.

Retrieval-Augmented Generation. The system pulls relevant snippets from your data (docs, support tickets, product specs, internal wikis) and feeds them to the model alongside the question, so answers are grounded in your real content instead of the model's general knowledge. We use RAG when the underlying data changes often or is too large to fit in a prompt. We skip it when a tighter approach (a small system prompt, a structured tool call) does the job.

The context window is how much input a model can hold at once: instructions, conversation history, and retrieved data. Bigger windows let you stuff more in, but two things matter. Cost scales with the tokens you actually send, not the ceiling. And quality degrades past roughly half the stated window even when content technically fits. We pick window size by the workload, not by the headline number.

We default to Claude (Anthropic) because we like the reasoning quality, the developer UX, the safety posture, and the zero-data-retention defaults. But we have hands-on experience with GPT-5, Gemini 2.5, Llama, and DeepSeek. If you have a preference for cost, latency, regional availability, or licensing reasons, we will factor it in.

AI is a tool you control, not magic. Most of the value comes from removing the boring middle of a workflow so the humans on either side can do better work. We are bullish on agentic systems for narrow, high-volume problems and conservative about anything that requires judgment in messy edge cases. We tell clients which one their problem is.

We default to Claude (Anthropic) for production builds. Reasoning quality compounds across multi-step agentic workflows, and Anthropic's safety, interpretability, and zero-data-retention posture matches the kind of work we ship. We will swap to a different model when there is a clear quality, cost, or compliance reason. We do not start from a model preference and back into a problem.

Most of our work removes work, not roles. The companies we partner with use the saved time to expand capacity, improve quality, or tackle projects that were previously parked. If a system would clearly displace a team, we say so up front so the client can plan for it like they would any other infrastructure decision.

No. We use providers with documented zero-data-retention guarantees (Anthropic API and equivalents). Your prompts, responses, and business data are never used to train a model. We will sign a DPA and a no-train clause as standard.

No. Anything an end customer interacts with discloses that it is an AI assistant when asked, and we encourage clients to disclose proactively. Our cold email work uses casualization techniques to read like a real person wrote it (because a real person reviewed it), but we do not put fake faces, fake names, or fake bios on AI agents that are talking to customers.

We do not build for spam farms, mass scraping for resale, deepfake or impersonation tools, or any application designed to deceive end users. We pass on offensive cyber work. We also pass when the math does not pencil out for the client, even if they want to spend the money.

In production we treat safety as an engineering problem, not a slogan. Tools have allow lists, agents have bounded action spaces, every prompt and response is audit-logged, sensitive data is redacted before it reaches a model, and high-stakes actions require a human in the loop by default. We track the OWASP LLM Top 10 and ship against it.

Orbit is headquartered in New Orleans, USA. Our network of senior engineers and operators spans three continents and six countries: the United States, Bosnia and Herzegovina, Croatia, Germany, Sweden, and Saudi Arabia. Coverage across these time zones means there is always someone awake when something is on fire.

Each location was chosen for a specific reason: relationships with senior people we have worked with for years, strong engineering depth in that region, language coverage, and time-zone overlap with where our clients live. We did not pick a country to claim a flag on a map. We picked the people first, and the geography followed.

Together our operating zones cover roughly 18 of 24 hours every day. North America (CST, EST, PST), Central and Northern Europe (CET, CEST), and Saudi Arabia (AST). Critical alerts page someone awake. Standard requests are answered within the next business window in your time zone.

Yes. Across the team we cover English, Bosnian, Croatian, Serbian, German, Swedish, and Arabic for review and prompt-tuning. Claude handles many more languages well at the model level, but we will not ship a production system in a language nobody on the team can read.

We can deploy your stack in EU regions for GDPR scope, in US regions for FedRAMP-adjacent work, or in Middle East regions where required. Anthropic via AWS Bedrock supports multiple regions and offers a HIPAA BAA. We can also self-host open-weight models on customer infrastructure when residency requirements demand it.

Yes. Our team locations are where we operate from, not who we sell to. We have shipped for clients in additional regions across North America, Europe, the UK, and APAC. Get on a call and we will tell you whether your time zone and language needs are inside our coverage envelope.

Sign up, pick a system from the marketplace, and connect your accounts. Most systems are live within 7 days, and you can add, pause, or remove them anytime. No calls required, though our team is around if you want a hand.

Most systems go live within 7 days of signing up: you add the system, connect your accounts, and we handle onboarding and the first runs. Adding more later is faster, since every system is already built and waiting in the marketplace.

No. Day to day operation is point and click in your dashboard. If you are technical and want source-code access, repo access, or your own cloud infrastructure, that path is available on Enterprise.

We monitor every system continuously and address most issues before you notice. Our global coverage means somebody is awake when a critical alert fires. Hosting, monitoring, bug fixes, performance tuning, and ongoing improvements are all included in your plan.

Yes. Most operators start with a single high-impact system, prove the ROI, then expand. Each system is independent and slots into the same dashboard.

You build your own plan: a $59/mo platform base plus the department modules you want (Sales, Marketing, Operations, Finance, Ecommerce, Intelligence, Cybersecurity). Pick everything and the whole suite caps at $599/mo. Unlimited agents on every plan, one shared credit pool, no setup fees, no contract, and a 7-day trial to start. Build it on the pricing page.

Your platform base covers the Assistant, one shared credit pool, the governance layer (autonomy levels, Approvals queue, kill switch), plus hosting, 24/7 monitoring, bug fixes, model upgrades, and support - with unlimited agents. Each department module you add unlocks its systems and adds monthly credits. Manual runs and the CRM never cost a credit.

Yes, on Enterprise. Beyond the catalog, Enterprise covers fully custom-built systems, a dedicated point of contact, a custom SLA, and a self-hosted or source-code option. Talk to us and we will scope it.

By default, in our managed cloud infrastructure encrypted at rest with AES-256 and in transit with TLS 1.3. We support customer-managed keys (BYOK), region pinning for GDPR or other residency requirements, and on-premises or VPC deployments when required.

No. We use providers with documented zero-data-retention guarantees. We will sign a no-train clause as part of every plan.

Yes, with the right pattern. For HIPAA we deploy through Anthropic on AWS Bedrock with a BAA. For PCI we keep card data out of the LLM path entirely (tokenization or vault references). For GDPR we use EU regions and pre-prompt PII redaction. Our Data Sensitivity Classifier tool will surface the right deployment pattern for your data type.

Yes. Every prompt, response, model call, tool call, and write action is logged with retention tuned to your compliance posture. Logs are immutable and exportable. The dashboard exposes search and filters for review.