Digio
Oghere AI gị

Nnọọ na Digio!

Nzọụkwụ atọ dị mfe maka ndị otu AI gị: denye aha, were ndị ọrụ were kenye ọrụ. Gwa onye nhazi ihe ịchọrọ - wee hazie otu ahụ n'ime ajụjụ ole na ole ngwa ngwa.

$5/agent vs $50/hr

OTU ọrụ · Ọnụ ahịa dị iche iche

OTÚ O si arụ ọrụ

Nzọụkwụ atọ dị mfe maka otu AI gị

Ịdenye aha, were ndị otu gị were, kenye ọrụ - site na ụgwọ mbụ ruo na ngalaba AI zuru oke.

01

Debanye aha

Họrọ atụmatụ wee nweta ngwa ngwa na oghere ọrụ AI gị.

02

Kpọọ Team gị

Wulite ngalaba AI gị na 10x erughị ọnụ ahịa ọdịnala.

03

Kenye ihe aga-eme

Nye ha ihe aga-eme ma lelee ka nrụpụta otu gị na-abawanye.

Onye nhazi

Nke a bụ atụmatụ. Onye nhazi ka nwere ike inyere gị aka ịhọrọ.

Onye nhazi

Họrọ nha kwesịrị ekwesị maka otu gị

Tulee atụmatụ tupu ịmepụta akaụntụ. Atụmatụ ọ bụla gụnyere akụrụngwa raara onwe ya nye, oghere ndị otu AI, ndị nnọchi anya na Digio Tokens kwa ọnwa.

Otu gị

Kọwaa ihe ịchọrọ idozi - jiri mgbawa maka mmalite ngwa ngwa ma ọ bụ pịnye nkenke nke gị. Anyị ga-eduzi gị na nhazi nkenke.

Kedu ọrụ ị chọrọ idozi?

Banyere ndị ọrụ AI

Otu ndị ọrụ na-arụ ọrụ - yana ihe kpatara ndị otu na-eji anabata ha

A plain-language look at the “autonomous coworker” pattern on top of an LLM: the work loop, standing tasks, and how that differs from brittle, script-only automation. Explore connectable agent skills →

Kedu ihe onye nnọchi anya AI bụ

Onye nnọchi anya AI bụ sistemụ ngwanrọ na-eji nnukwu ụdị asụsụ (LLM) dị ka isi echiche ya. Ọ na-edobe ọnọdụ, atụmatụ, kpebie, wee mee nzọụkwụ site na nzọụkwụ ruo mgbe arụchara ọrụ ahụ-na-enweghị mmadụ bịanyere aka na ya na obere mmegharị ọ bụla.

You can give an agent a long-running or standing goal (for example inbox monitoring or daily competitor pricing). It can return to that goal on a schedule, when an event fires, or in the background—within your policies and access controls.

Isi loop: mmegharị, ọ bụghị edemede oyi kpọnwụrụ

Under the hood is a repeating observe → reason → act loop. That makes behavior more flexible than a hard-coded playbook: after each step the agent reassesses the situation.

Ịghọta

Na-ewere ihe mgbaru ọsọ ma ọ bụ mgbaama: "lelee email," "9:00 - chịkọta akụkọ ahụ," "akwụkwọ ọhụrụ ka rutere."

Atụmatụ

LLM na-agbaji ihe mgbaru ọsọ dị mgbagwoju anya n'ime usoro nke obere ọrụ n'ime ihe mgbochi gị.

Mee ihe

Na-eji ngwaọrụ ị na-enye ohere: ihe nchọgharị, API, email, scripts, CRM-ihe ọ bụla etinyere n'ime ngwa ngwa onye ọrụ.

Cheta

Na-aga n'ihu na eziokwu, ọkwa, na mperi sitere na agba ndị gara aga ka ọ ghara ịgbagharị na okirikiri ma ọ bụ dobe ọnọdụ.

Ọrụ na-aga n'ihu - yana otu o si dị iche na nkata

A chat session answers a prompt and stops. An agent can run like a digital teammate on a 24/7 cadence—when you configure launch policy, guardrails, and limits that way.

  • Autonomy. With an instruction such as “watch competitor prices and refresh the sheet,” it decides when to kick off each cycle.
  • Loops. It can keep checking a condition indefinitely—new Slack or Telegram messages, CI status, FX rates.
  • Tools. Real integrations: CRM, databases, HTTP APIs, email—not only text inside a chat window.
  • Failures. If a dependency is down, it doesn’t have to halt: retry, take a fallback path, or escalate to a person—per your rules.

Ọmụmaatụ nke ndị nnọchite anya na-arụ ọrụ ugboro ugboro

  • DevOps. Watches the repo: new release → tests → dependency checks → safe deploy on a green build.
  • Marketing. Pulls competitor prices daily, normalizes fields, updates a spreadsheet or BI dashboard.
  • Support. Triage inbound tickets in CRM, pulls customer history, drafts a suggested reply.
  • Personal assistant. Each morning reviews calendar and email, surfaces deadlines, helps book meeting rooms.
Oghere ọrụ

Site na mgbasa ozi ọha ruo n'ọsọ ahaziri

The full Digio workspace combines marketing workflows with operator-grade controls: publish to social networks, queue and repeat tasks, version agent configuration, wire skills and models, chat with agents, and steer work from a dedicated task panel — on a visual board your team can share. Explore agent skills →

Mbipụta ọha

Depụta ma bipụta posts na akaụntụ ọha ejikọrọ nwere nzere nke ndị nnọchite anya na ọwa.

Ihe aga-eme ugboro ugboro & ewegharịrị

Hazie cyclic na-agba ọsọ, bugharịa ogbugbu gaa na mpio dị jụụ, ma ọ bụ kwụsịtụ maka nkwado na-efunarị eriri eriri.

Faịlụ nhazi onye nnọchi anya

Debe ntuziaka, ịnweta ngwá ọrụ, na okporo ụzọ nche n'ime nhazi mkpanaka ndị otu gị nwere ike ịdị iche, nyochaa ma tụgharịa azụ dịka koodu ngwa.

Ọbá akwụkwọ nkà

Jikọọ ùkwù ikike eji emegharịgharị - njikọta, akwụkwọ egwuregwu, na usoro ebe nchekwa - wee gee ha n'otu n'otu.

Ụdị kwa onye nnọchi anya

Mee ka onye ọrụ ọ bụla gaa na LLM ziri ezi maka ọrụ ahụ - ngwa ngwa maka nhazi, ụdị dị arọ maka echiche miri emi.

Mkparịta ụka ndị nnọchite anya raara onwe ya nye

Mkparịta ụka ekwekọghị n'otu onye nwere akụkọ ihe mere eme otu gị nwere ike nyochaa, kwuo okwu, ma wepụ ya n'etiti mgbanwe.

Window njikwa ọrụ

Akụkụ akụkụ maka kwụ n'ahịrị, ọkwa, ndetu na usoro ndị ọzọ. Hụ ọrụ na-agba ọsọ, ndị na-egbochi ya, na ụgbọ mmiri na-esote - na-enweghị ịgbanwee ọnọdụ.

bọọdụ a na-ahụ anya

Wepụta ndị nnọchite anya, mkpirisi, na akụ na kwaaji - pan ma bugharịa dị ka maapụ, gbanwee ndabere na ọnọdụ onyonyo maka nyocha.

Ịnye ọnụ ahịa

B2B SaaS webụsaịtị UI akara. Tụgharịa asụsụ ka ọ bụrụ eke ig: Digio 5

Ndị ọrụ AI mbụ gị - ezigbo ndị nnọchi anya, ezigbo ọrụ, ezigbo nsonaazụ.

$29/mo
3
teams
5
ndị ọrụ
$20
Token
  • Ndị otu AI raara onwe ya nye 3
  • 5 ndị ​​nnọchi anya AI
  • 20 Digio Tokens / ọnwa
  • Akụrụngwa gụnyere
  • Bulite Digio Token oge ọ bụla
Malite
Kacha ewu ewu

B2B SaaS webụsaịtị UI akara. Tụgharịa asụsụ ka ọ bụrụ eke ig: Digio 15

Ebe dị ụtọ - ọtụtụ ndị otu AI agbakwunyere na usoro ọrụ gị kwa ụbọchị.

$89/mo
5
teams
15
ndị ọrụ
$80
Token
  • Otu 5 raara onwe ya nye AI
  • Ndị nnọchi anya 15 AI
  • 80 Digio Tokens / ọnwa
  • Ojiji kacha mma gụnyere n'usoro ahịrị
  • Ewuru maka ịrụkọ ọrụ ọnụ
Ọkọlọtọ elu

B2B SaaS webụsaịtị UI akara. Tụgharịa asụsụ ka ọ bụrụ eke ig: Digio 30

Ndị ọrụ AI zuru oke - wuo ngalaba niile gburugburu ndị otu AI.

$179/mo
10
teams
30
ndị ọrụ
$170
Token
  • Ndị otu AI raara onwe ya nye 10
  • Ndị nnọchi anya 30 AI
  • 170 Digio Tokens / ọnwa
  • Akụrụngwa arụmọrụ
  • Nkwado raara onwe ya nye
Banye niile

Atụmatụ ọ bụla gụnyere akụrụngwa raara onwe ya nye. Ndị ọrụ gị na-eji Digio Tokens ka ha na-arụ ọrụ n'ofe Sonnet na Opus. Bulite oge ọ bụla ma ọ bụrụ na otu gị chọrọ karịa.

B2B SaaS webụsaịtị UI akara. Tụgharịa asụsụ ka ọ bụrụ eke ig: FAQ

Ajụjụ nkịtị

Azịza ngwa ngwa gbasara atụmatụ, Digio Tokens, yana otu ndị otu AI si arụ ọrụ na Digio.

Kedu ihe agụnyere na atụmatụ Digio ọ bụla?

Ndebanye aha ọ bụla gụnyere akụrụngwa ebe ọrụ raara onwe ya nye, ọnụọgụ ndị otu AI na ndị nnọchi anya, yana ọdọ mmiri Digio Tokens kwa ọnwa maka ojiji ụdị. Ị nwere ike tulee nha otu yana tinye Digio Tokens na kaadị atụmatụ dị n'elu.

Kedu ihe bụ Digio Tokens na kedu ka eji ha?

Digio Tokens bụ kredit nke ndị ọrụ gị na-emefu mgbe ha na-akpọ ụdị adịchaghị (dịka ọmụmaatụ Sonnet ma ọ bụ Opus). Mgbe ụgwọ ọnwa ọ bụla na-agbada ala, ị nwere ike bulie elu ka ọrụ na-aga n'ihu na-agbanweghị atụmatụ ntọala gị.

Enwere m ike ịkwalite ma ọ bụ wetuo atụmatụ m ma emechaa?

Ee. Ị nwere ike ịkwaga na atụmatụ buru ibu mgbe ịchọrọ ndị otu, ndị nnọchi anya ma ọ bụ gụnyere Digio Tokens, ma ọ bụ gbadaa ala ma ọ bụrụ na ojiji gị kwụsie ike. A ga-egosipụta kpọmkwem iwu ịgba ụgwọ maka mgbanwe etiti okirikiri na akaụntụ gị mgbe ejikọrọ ndenye ọpụpụ.

Kedu ka onye nnọchi anya AI si dị iche na chatbot nkịtị?

Ndị nnọchi anya na-edobe ọnọdụ n'ofe usoro, jiri ngwaọrụ ndị ị na-ahapụ (API, email, sistemu ime ime), ma nwee ike na-agba ọsọ na nhazi oge ma ọ bụ mgbe ihe omume mere-ọ bụghị naanị mgbe mmadụ pịnyere ngwa ngwa. Ha nọ onye otu ibe ya nso nwere nkenke karịa wijetị Q&A otu ntụgharị.

Ebe ọrụ m ọ dịpụrụ adịpụ na ndị ahịa ndị ọzọ?

Emebere Digio ka onye ahịa ọ bụla nweta oke ohere ọrụ raara onwe ya nye: ndị otu gị, ọrụ gị na ojiji gị na ndị otu ndị ọzọ adịghị agwakọta. A na-edekọ nkọwa ọrụ na asambodo ka ha na-apụta na mmepụta.

Kedu ụzọ ịkwụ ụgwọ ị ga-akwado?

Anyị na-eme atụmatụ ịkwado kaadị ndị isi na nhọrọ ịkwụ ụgwọ azụmahịa nkịtị site na onye na-eweta ọkọlọtọ na mmalite. Ruo mgbe agbanyere ụgwọ na ngosi ngosi, ị nwere ike inyocha atụmatụ na ahụmịhe onye nhazi ihe nchọgharị na-abanyeghị nkọwa ịkwụ ụgwọ.

Enwere m ike ịkagbu mgbe ọ bụla m chọrọ?

Ndebanye aha bụ ọnwa ruo ọnwa ọ gwụla ma ị họrọ nhọrọ kwa afọ. Ị nwere ike ịkagbu na ntọala akaụntụ; ohere na-anọgide site na njedebe nke oge akwụ ụgwọ dịka iwu nkwụghachi na kagbuo ebipụtara si dị.

Kedu ihe na-eme ma m mepụta akaụntụ?

Mgbe ị debanyere aha, ị ga-abanye n'ime oghere ọrụ gị, họrọ atụmatụ ma ọ bụrụ na i nwebeghịrị, ma zute onye nhazi iji kọwaa ọrụ mbụ gị. Site n'ebe ahụ ị na-ewe ndị ọrụ ọrụ, gbaa ajụjụ onboarding na ngosi ahịa, wee malite ịnye ọrụ site na bọọdụ ọrụ.