Marine Coat€89
AI that your team actually uses, not just pays for
AI works when your team is ready for it. Most organisations skip that part. We don't. We work with leadership to make sure your team knows how to use AI before, during, and long after rollout.
AI that your team actually uses, not just pays for
AI works when your team is ready for it. Most organisations skip that part. We don't. We work with leadership to make sure your team knows how to use AI before, during, and long after rollout.
AI that your team actually uses, not just pays for
AI works when your team is ready for it. Most organisations skip that part. We don't. We work with leadership to make sure your team knows how to use AI before, during, and long after rollout.
New AI tools appear every week. Adopting one wrong wastes months and moves nothing.
Companies that work with us see real adoption rates of [X]%
A process made straightforward by design
A process made straightforward by design
A process made straightforward by design
AI adoption that sticks
AI adoption that sticks
AI adoption that sticks
We know the tools we recommend.
We don't recommend tools we don't know deeply. Every platform, framework, and AI tool we bring into an engagement is one we've worked with hands-on.
defaultshop.ai
MARINE
⌕raincoat
cart0
4 results for “raincoat”
Harbor Anorak€119
Storm Trench€149
North Shell€96
searching for 'raincoat ≤ €100'
Agent task·Buy a sustainable raincoat for the Berlin trip · €100 cap
claude — fish — 100×30
Our technology stack
hubblrv0.4.2·stack categories
languages
·
name
used in
●TypeScriptfrontend, edge runtimes, agent SDKs
●PythonFastAPI services, data pipelines, agents
●Gohigh-throughput services, infra glue
●SQLPostgres-first · Atlas migrations · dbt
●BashCI, deploys, day-to-day glue
ai
·
name
used in
●Claude CodeAI pair-programmer in the terminal
●MCP serversexpose internal tools to agents
●Gemini SDKlong-context multimodal, planning
●MastraTypeScript agent SDK
●Vercel AI SDKstreaming + tool-use on the edge
●Vercel Chat SDKproduction chat scaffold · resumable streams
●AI Gatewaymodel routing, observability, budgets
●v0AI-built UI scaffolds · ship to Vercel
●Langfuseproduction tracing + evals
●pgvectorRAG straight in Postgres
agentic commerce
·
name
used in
●Agent Commerce Protocolopen spec for agent-to-merchant transactions
●Stripe Agent Toolkitagent-issued payments + checkout APIs
●Browserbaseheadless browser-as-a-service for agents
●StagehandPlaywright + LLM, structured browser control
●Computer UseAnthropic desktop control · agentic shopping flows
●LangGraphagent state machines · tool routing
●MCP serversexpose product catalog + checkout to agents
backend
·
name
used in
●FastAPIPython · async · Pydantic-typed
●SQLAlchemy 2async ORM · asyncpg
●Pydanticschemas + validation everywhere
●Postgres 16primary store · jsonb · pgvector
●Atlasdeclarative schema · HCL migrations
●Connect RPCHTTP/JSON · gRPC · gRPC-Web from one .proto
●Rediscache · queues · pubsub
frontend
·
name
used in
●React + Vitefast dev loop, modern build
●Tailwind CSSdesign system in classes
●Radix UIaccessible primitives
●shadcn/uicopy-pastable components
●Framer Motioninteraction + transitions
●React Nativeshared codebase across iOS/Android
devops
·
name
used in
●Turborepomonorepo · cached pipelines
●pnpm + uvfast install for JS + Python
●Docker Composelocal stack in one command
●AWSprimary cloud · prod workloads
●Google Clouddata + ML stack
●Terraforminfra-as-code
●Vercelmarketing + edge functions
quality
·
name
used in
●TypeScriptstrict mode, every file
●Ruff + MypyPython lint + types
●BufProtobuf lint + breaking-change checks
●Pytest · Vitestunit + integration
●Playwrightbrowser e2e + smoke tests
commerce
·
name
used in
●Shopifyheadless storefronts
●commercetoolsenterprise composable
●Contentfulheadless CMS
●emdash CMSgit-native headless CMS · TS-first
●Algoliasearch + recs
product
·
name
used in
●Linearissues, cycles
●Notiondocs + roadmaps
●Figmadesign + prototypes
●Dovetailuser research
← / → switch category·scroll
Explorer
▾apps
▾web
▾src
▾components
TSSearchPanel.tsx
▾services
▾api
▾app
Pymain.py
▾models
Pyaccount.py
▾agent
Pymcp_server.py
▾proto
▾api
▾v1
·account.proto
▾db
·schema.hcl
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
import { useState } from "react"
import * as Dialog from "@radix-ui/react-dialog"
import { motion } from "framer-motion"
import { Search } from "lucide-react"
import { useAccountSearch } from "@/lib/api/account"
import { cn } from "@/lib/cn"
export function SearchPanel() {
const [open, setOpen] = useState(false)
const { data, isLoading } = useAccountSearch()
return (
<Dialog.Root open={open} onOpenChange={setOpen}>
<Dialog.Trigger
className={cn(
"inline-flex items-center gap-2 rounded-md",
"border border-zinc-200 bg-white px-3 py-1.5 text-sm",
"hover:bg-zinc-50"
)}
>
<Search className="size-4" />
Search…
</Dialog.Trigger>
<Dialog.Portal>
<Dialog.Overlay asChild>
<motion.div initial={{ opacity: 0 }} animate={{ opacity: 0.5 }} />
</Dialog.Overlay>
</Dialog.Portal>
</Dialog.Root>
)
}
⎇ mainLn 4, Col 28TSXUTF-8spaces: 2
We know the tools we recommend.
We don't recommend tools we don't know deeply. Every platform, framework, and AI tool we bring into an engagement is one we've worked with hands-on.
defaultshop.ai
MARINE
⌕raincoat
cart0
4 results for “raincoat”
Marine Coat€89
Harbor Anorak€119
Storm Trench€149
North Shell€96
searching for 'raincoat ≤ €100'
Agent task·Buy a sustainable raincoat for the Berlin trip · €100 cap
claude — fish — 100×30
Our technology stack
hubblrv0.4.2·stack categories
languages
·
name
used in
●TypeScriptfrontend, edge runtimes, agent SDKs
●PythonFastAPI services, data pipelines, agents
●Gohigh-throughput services, infra glue
●SQLPostgres-first · Atlas migrations · dbt
●BashCI, deploys, day-to-day glue
ai
·
name
used in
●Claude CodeAI pair-programmer in the terminal
●MCP serversexpose internal tools to agents
●Gemini SDKlong-context multimodal, planning
●MastraTypeScript agent SDK
●Vercel AI SDKstreaming + tool-use on the edge
●Vercel Chat SDKproduction chat scaffold · resumable streams
●AI Gatewaymodel routing, observability, budgets
●v0AI-built UI scaffolds · ship to Vercel
●Langfuseproduction tracing + evals
●pgvectorRAG straight in Postgres
agentic commerce
·
name
used in
●Agent Commerce Protocolopen spec for agent-to-merchant transactions
●Stripe Agent Toolkitagent-issued payments + checkout APIs
●Browserbaseheadless browser-as-a-service for agents
●StagehandPlaywright + LLM, structured browser control
●Computer UseAnthropic desktop control · agentic shopping flows
●LangGraphagent state machines · tool routing
●MCP serversexpose product catalog + checkout to agents
backend
·
name
used in
●FastAPIPython · async · Pydantic-typed
●SQLAlchemy 2async ORM · asyncpg
●Pydanticschemas + validation everywhere
●Postgres 16primary store · jsonb · pgvector
●Atlasdeclarative schema · HCL migrations
●Connect RPCHTTP/JSON · gRPC · gRPC-Web from one .proto
●Rediscache · queues · pubsub
frontend
·
name
used in
●React + Vitefast dev loop, modern build
●Tailwind CSSdesign system in classes
●Radix UIaccessible primitives
●shadcn/uicopy-pastable components
●Framer Motioninteraction + transitions
●React Nativeshared codebase across iOS/Android
devops
·
name
used in
●Turborepomonorepo · cached pipelines
●pnpm + uvfast install for JS + Python
●Docker Composelocal stack in one command
●AWSprimary cloud · prod workloads
●Google Clouddata + ML stack
●Terraforminfra-as-code
●Vercelmarketing + edge functions
quality
·
name
used in
●TypeScriptstrict mode, every file
●Ruff + MypyPython lint + types
●BufProtobuf lint + breaking-change checks
●Pytest · Vitestunit + integration
●Playwrightbrowser e2e + smoke tests
commerce
·
name
used in
●Shopifyheadless storefronts
●commercetoolsenterprise composable
●Contentfulheadless CMS
●emdash CMSgit-native headless CMS · TS-first
●Algoliasearch + recs
product
·
name
used in
●Linearissues, cycles
●Notiondocs + roadmaps
●Figmadesign + prototypes
●Dovetailuser research
← / → switch category·scroll
Explorer
▾apps
▾web
▾src
▾components
TSSearchPanel.tsx
▾services
▾api
▾app
Pymain.py
▾models
Pyaccount.py
▾agent
Pymcp_server.py
▾proto
▾api
▾v1
·account.proto
▾db
·schema.hcl
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
import { useState } from "react"
import * as Dialog from "@radix-ui/react-dialog"
import { motion } from "framer-motion"
import { Search } from "lucide-react"
import { useAccountSearch } from "@/lib/api/account"
import { cn } from "@/lib/cn"
export function SearchPanel() {
const [open, setOpen] = useState(false)
const { data, isLoading } = useAccountSearch()
return (
<Dialog.Root open={open} onOpenChange={setOpen}>
<Dialog.Trigger
className={cn(
"inline-flex items-center gap-2 rounded-md",
"border border-zinc-200 bg-white px-3 py-1.5 text-sm",
"hover:bg-zinc-50"
)}
>
<Search className="size-4" />
Search…
</Dialog.Trigger>
<Dialog.Portal>
<Dialog.Overlay asChild>
<motion.div initial={{ opacity: 0 }} animate={{ opacity: 0.5 }} />
</Dialog.Overlay>
</Dialog.Portal>
</Dialog.Root>
)
}
⎇ mainLn 4, Col 28TSXUTF-8spaces: 2
We know the tools we recommend.
We don't recommend tools we don't know deeply. Every platform, framework, and AI tool we bring into an engagement is one we've worked with hands-on.
defaultshop.ai
MARINE
⌕raincoat
cart0
4 results for “raincoat”
Marine Coat€89
Harbor Anorak€119
Storm Trench€149
North Shell€96
searching for 'raincoat ≤ €100'
Agent task·Buy a sustainable raincoat for the Berlin trip · €100 cap
claude — fish — 100×30
Our technology stack
hubblrv0.4.2·stack categories
languages
·
name
used in
●TypeScriptfrontend, edge runtimes, agent SDKs
●PythonFastAPI services, data pipelines, agents
●Gohigh-throughput services, infra glue
●SQLPostgres-first · Atlas migrations · dbt
●BashCI, deploys, day-to-day glue
ai
·
name
used in
●Claude CodeAI pair-programmer in the terminal
●MCP serversexpose internal tools to agents
●Gemini SDKlong-context multimodal, planning
●MastraTypeScript agent SDK
●Vercel AI SDKstreaming + tool-use on the edge
●Vercel Chat SDKproduction chat scaffold · resumable streams
●AI Gatewaymodel routing, observability, budgets
●v0AI-built UI scaffolds · ship to Vercel
●Langfuseproduction tracing + evals
●pgvectorRAG straight in Postgres
agentic commerce
·
name
used in
●Agent Commerce Protocolopen spec for agent-to-merchant transactions
●Stripe Agent Toolkitagent-issued payments + checkout APIs
●Browserbaseheadless browser-as-a-service for agents
●StagehandPlaywright + LLM, structured browser control
●Computer UseAnthropic desktop control · agentic shopping flows
●LangGraphagent state machines · tool routing
●MCP serversexpose product catalog + checkout to agents
backend
·
name
used in
●FastAPIPython · async · Pydantic-typed
●SQLAlchemy 2async ORM · asyncpg
●Pydanticschemas + validation everywhere
●Postgres 16primary store · jsonb · pgvector
●Atlasdeclarative schema · HCL migrations
●Connect RPCHTTP/JSON · gRPC · gRPC-Web from one .proto
●Rediscache · queues · pubsub
frontend
·
name
used in
●React + Vitefast dev loop, modern build
●Tailwind CSSdesign system in classes
●Radix UIaccessible primitives
●shadcn/uicopy-pastable components
●Framer Motioninteraction + transitions
●React Nativeshared codebase across iOS/Android
devops
·
name
used in
●Turborepomonorepo · cached pipelines
●pnpm + uvfast install for JS + Python
●Docker Composelocal stack in one command
●AWSprimary cloud · prod workloads
●Google Clouddata + ML stack
●Terraforminfra-as-code
●Vercelmarketing + edge functions
quality
·
name
used in
●TypeScriptstrict mode, every file
●Ruff + MypyPython lint + types
●BufProtobuf lint + breaking-change checks
●Pytest · Vitestunit + integration
●Playwrightbrowser e2e + smoke tests
commerce
·
name
used in
●Shopifyheadless storefronts
●commercetoolsenterprise composable
●Contentfulheadless CMS
●emdash CMSgit-native headless CMS · TS-first
●Algoliasearch + recs
product
·
name
used in
●Linearissues, cycles
●Notiondocs + roadmaps
●Figmadesign + prototypes
●Dovetailuser research
← / → switch category·scroll
Explorer
▾apps
▾web
▾src
▾components
TSSearchPanel.tsx
▾services
▾api
▾app
Pymain.py
▾models
Pyaccount.py
▾agent
Pymcp_server.py
▾proto
▾api
▾v1
·account.proto
▾db
·schema.hcl
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
import { useState } from "react"
import * as Dialog from "@radix-ui/react-dialog"
import { motion } from "framer-motion"
import { Search } from "lucide-react"
import { useAccountSearch } from "@/lib/api/account"
import { cn } from "@/lib/cn"
export function SearchPanel() {
const [open, setOpen] = useState(false)
const { data, isLoading } = useAccountSearch()
return (
<Dialog.Root open={open} onOpenChange={setOpen}>
<Dialog.Trigger
className={cn(
"inline-flex items-center gap-2 rounded-md",
"border border-zinc-200 bg-white px-3 py-1.5 text-sm",
"hover:bg-zinc-50"
)}
>
<Search className="size-4" />
Search…
</Dialog.Trigger>
<Dialog.Portal>
<Dialog.Overlay asChild>
<motion.div initial={{ opacity: 0 }} animate={{ opacity: 0.5 }} />
</Dialog.Overlay>
</Dialog.Portal>
</Dialog.Root>
)
}
⎇ mainLn 4, Col 28TSXUTF-8spaces: 2
A fast moving team, fully enabled to deliver end to end.
In the new engineering era it's crucial that engineers are empowered to discover, scope and deliver features end to end while reducing dependencies to others. And we are a small team of opinionated people.
A fast moving team, fully enabled to deliver end to end.
In the new engineering era it's crucial that engineers are empowered to discover, scope and deliver features end to end while reducing dependencies to others. And we are a small team of opinionated people.
A fast moving team, fully enabled to deliver end to end.
In the new engineering era it's crucial that engineers are empowered to discover, scope and deliver features end to end while reducing dependencies to others. And we are a small team of opinionated people.
Testimonial
Something we think about
Invested in Business Goals
To build a successful product organisation, it is essential senior leadership needs to find clarity on the business strategy and tools to communicate that to the teams.
Reduce Complexity to ship faster
The monorepo is back and we're here for it. Shipping fast means cutting technical setup complexity and human complexity, controlling what your team (including your agents) can consume and own.
Rich in experience, agnostic in language.
The best people you can have are those eager to learn, eager to unlearn, and who've seen software products break at scale. With agentic engineering, the right instincts matter more than which language you know.
Something we think about
Invested in Business Goals
To build a successful product organisation, it is essential senior leadership needs to find clarity on the business strategy and tools to communicate that to the teams.
Reduce Complexity to ship faster
The monorepo is back and we're here for it. Shipping fast means cutting technical setup complexity and human complexity, controlling what your team (including your agents) can consume and own.
Rich in experience, agnostic in language.
The best people you can have are those eager to learn, eager to unlearn, and who've seen software products break at scale. With agentic engineering, the right instincts matter more than which language you know.
Something we think about
Invested in Business Goals
To build a successful product organisation, it is essential senior leadership needs to find clarity on the business strategy and tools to communicate that to the teams.
Reduce Complexity to ship faster
The monorepo is back and we're here for it. Shipping fast means cutting technical setup complexity and human complexity, controlling what your team (including your agents) can consume and own.
Rich in experience, agnostic in language.
The best people you can have are those eager to learn, eager to unlearn, and who've seen software products break at scale. With agentic engineering, the right instincts matter more than which language you know.
Questions you might have
01
We already have some AI tools in place, do we still need this?
We understand that you've already made investments here. This isn't about starting over, it's about auditing what's actually being used, closing the gaps in adoption, and building the processes that turn scattered usage into something consistent and measurable.
02
What do investors and acquirers actually look for when it comes to AI?
Consistent usage across the organisation, clear governance, documented processes, and measurable business impact. Anything that looks like it was deployed for optics rather than operations is a flag worth addressing.
03
What if our team is resistant to change?
That's normal and we plan for it. Resistance usually comes from not understanding why the change matters, our approach is built around making that case clearly before anything gets rolled out.
04
Do you recommend specific tools or are you tool agnostic?
Tool agnostic. We recommend what's right for your organisation and your workflows.
Questions you might have
01
We already have some AI tools in place, do we still need this?
We understand that you've already made investments here. This isn't about starting over, it's about auditing what's actually being used, closing the gaps in adoption, and building the processes that turn scattered usage into something consistent and measurable.
02
What do investors and acquirers actually look for when it comes to AI?
Consistent usage across the organisation, clear governance, documented processes, and measurable business impact. Anything that looks like it was deployed for optics rather than operations is a flag worth addressing.
03
What if our team is resistant to change?
That's normal and we plan for it. Resistance usually comes from not understanding why the change matters, our approach is built around making that case clearly before anything gets rolled out.
04
Do you recommend specific tools or are you tool agnostic?
Tool agnostic. We recommend what's right for your organisation and your workflows.
Questions you might have
We already have some AI tools in place, do we still need this?
We understand that you've already made investments here. This isn't about starting over, it's about auditing what's actually being used, closing the gaps in adoption, and building the processes that turn scattered usage into something consistent and measurable.
What do investors and acquirers actually look for when it comes to AI?
What if our team is resistant to change?
Do you recommend specific tools or are you tool agnostic?
Final CTA
Related services
Related services
I care about software that runs in production, not software that looks good in a demo.
With AI that matters more than ever. The interesting work starts after the prototype: wiring agents into real processes, owning the edge cases, and making sure it still works next month.
We stay until it is in your hands and your team can run it without us.
Xaver Ebner
,
Managing Director at HUBBLR Technologies
I care about software that runs in production, not software that looks good in a demo.
With AI that matters more than ever. The interesting work starts after the prototype: wiring agents into real processes, owning the edge cases, and making sure it still works next month.
We stay until it is in your hands and your team can run it without us.
Xaver Ebner
,
Managing Director at HUBBLR Technologies
I care about software that runs in production, not software that looks good in a demo.
With AI that matters more than ever. The interesting work starts after the prototype: wiring agents into real processes, owning the edge cases, and making sure it still works next month.
We stay until it is in your hands and your team can run it without us.
Xaver Ebner
,
Managing Director at HUBBLR Technologies
