Your business runs on manual hours. Let's take them back.
Somewhere in your operation, one process is quietly eating the most time and headcount. Support tickets after hours. Leads going cold overnight. Documents typed by hand. Most companies answer that with another per-seat subscription, then bend their process to fit it. GenAgent takes the process itself. GenAgent Max takes the whole lifecycle. Both are built on your data, on your infrastructure, owned by you.
One process, or the whole business.
The difference isn't scale for its own sake. It's whether you're fixing the one bottleneck that hurts most, or replacing the way work moves through your entire company.
GenAgent
GenAgent implements a single process inside your business: the one eating most of your manual hours, or creating a dependency on people you can't scale.
Think of the CSM or support desk that has to be staffed 24/7 because a lead won't wait until Monday. Think of the person retyping the same document fields every day. That work has a shape, and an agent can hold it.
Which process? That's not a guess. A 7-day GenSprint maps where your money and hours are actually burning, then names the one workflow where an agent pays back fastest.
- One workflow is visibly consuming your team's week
- You're staffing hours, not outcomes, to stay responsive
- You want proof before a wider commitment
- You need a fast, affordable place to start
GenAgent Max
GenAgent Max is not another dashboard bolted onto the four tools you already ignore. It's a full lifecycle suite connected across your business. The agents work together, share one knowledge model, and cover the whole path a job takes from first touch to closed.
If you're still running on paper, spreadsheets, or a generic CRM, CMS or helpdesk that was never built for how you actually operate, this is the edge. The incumbent tools price per seat, per contact, per ticket, so the bill grows precisely as you succeed. Their roadmap is not yours, and when they deprecate a feature or reprice a tier, your workflow moves with them. You stop bending your business around someone else's software.
Built on LLM + RAG you own. Your knowledge, your guardrails, your infrastructure. Shared secure server or fully on-premise.
- Work still moves on paper, spreadsheets or manual handoffs
- Your CRM/CMS forces process it was never designed for
- Multiple departments hit the same bottlenecks
- You want the capability owned, not rented forever
The tools you're renting were built for someone else's business.
There is nothing wrong with buying software. There is something wrong with paying more every year for a workflow you still have to work around.
Priced by headcount, not outcome. Every new hire raises the bill, and the fields you actually need sit behind a higher tier or a paid integration.
Charged per agent or per resolution. The repetitive tickets, the ones a model answers well, are exactly the ones you are paying humans hourly to clear.
Flexible until your process is genuinely specific. Then you are writing workarounds, and the workaround becomes the system of record.
A chat box bolted onto a product that was not designed for it, trained on generic data, with no access to what your company actually knows.
A GenAgent is engineered once, against your data, and the capability stays yours. The economics run the other way: it does not get more expensive as you grow into it.
Not sure which one you need? That's what GenSprint is for.
Seven days. We sit with your team and your stack, find where cost is leaking, and tell you honestly whether it's a single agent, the full suite, or just better process. You keep the costed roadmap either way, no commitment to continue.
Each agent does one job properly.
Every bird is a specialist tuned to one class of work, named for the instinct it mirrors. Deploy one as a GenAgent, or the whole flock as GenAgent Max. Each maps to a real Genboot build. The proof line under each card is an actual project, not a case study we invented.
Owl
Owl ingests meeting transcripts, threads and status updates, extracts commitments and owners with an LLM, then writes them into your tracker as structured tickets (epics, assignees, due dates, dependencies) so the board stays current without a human transcribing it.
Eagle
Eagle syncs mail, calendar and tasks, classifies every inbound message for priority, urgency and reply-type, then drafts thread-aware responses in the user's own writing style. A scheduled job produces a morning briefing with the day's priorities and a suggested first move.
Falcon
Falcon watches your inbound channels and responds the moment a lead lands, qualifying against your criteria, answering first questions from your own material, and booking the next step straight into a calendar. Sequences continue automatically until the lead engages or exits.
Hawk
Hawk parses agreements and regulated documents across multiple model providers with fallback, extracts obligations, dates and risk clauses, checks them against your policy rules, and writes an immutable audit trail of every read, decision and approval, with role-based access so people only see what they're cleared for.
Raven
Raven chunks and embeds your documents into a vector index with permissions and metadata attached, then answers questions using retrieval-augmented generation, grounded only in your own material and never the open internet. Answers cite their source, and an admin portal handles ongoing ingestion.
Swift
Swift parses natural-language availability into ranked slots, emails participants, reads their replies (confirm, decline or counter-propose), resolves the conflict, and books the event. It runs as a background job, so it keeps working while everyone gets on with their day.
Heron
Heron runs uploads through a multi-model extraction pipeline, with OCR fallback for low-confidence fields, then merges and validates the results against the expected schema before writing them into your systems. Anything below the confidence threshold is routed to a human rather than guessed.
Kestrel
Kestrel answers repetitive, well-defined queries straight from your knowledge base (order status, tracking, policy, how-to), then classifies everything else by intent and urgency, and routes only genuine exceptions to a human with the context already attached.
What you're actually investing in.
Same engineering, different scope. Compare how the two tiers behave across the things that matter, then see what each one looked like in a real build.
GenAgent
GenAgent Max
A single workflow: the one burning most of your manual hours, identified in a GenSprint.
The full path work takes through your business, across departments and handoffs.
One bird from the Aviary, tuned to that process.
The flock. Agents that share one knowledge model and hand work to each other.
One bottleneck is visible and painful, and you want proof before going wider.
You still run on paper, spreadsheets, or a generic CRM/CMS that fights your process.
Grounded in the data that workflow touches.
Your whole knowledge base (methodologies, playbooks, work samples), permission-aware.
Shared secure server or on-premise.
Shared secure server or fully on-premise, with audit trails across every department.
You own the deployment. Not a per-seat rental that climbs every renewal.
LLM + RAG you own outright. The capability stays yours, on your infrastructure.
Single-agent builds
Multi-agent & platform builds
We deployed document intelligence into their transaction platform: agreements parsed across multiple model providers, role-based access, and a compliance audit trail behind every action.
A RAG knowledge platform with semantic search over their proprietary research, plus an admin portal so their team keeps feeding the model without engineering involvement.
Two agents working together: outreach responds to inbound leads immediately, and scheduling resolves availability and books the tour without a coordinator.
A closer shape to Max. A router plans which specialist handles each request across email, calendar, tasks and knowledge, composing the result with guardrails and logging.
Intelligent form automation. Extraction is validated against expected structure, and low-confidence fields route to a human rather than getting guessed.
A support agent handles order and tracking queries straight from the knowledge base, with multi-role portals behind it. Everything else routes to a person with context already attached.
Find the process that's costing you most.
Start with a 7-day GenSprint. We'll map where the hours and money are going, then tell you which agent (if any) pays back fastest. You keep the roadmap either way.