Utaalamu / Kwa karibu
Wasaidizi wa AI na mifumo ya maarifa
Wasaidizi wa wateja na timu wanaojibu kutokana na maarifa yenu — na vyanzo, ulinzi na njia ya binadamu.
Fursa
Fanya hatua inayofuata
hatua bora zaidi.
Buyers and users expect an answer the moment they ask. Support inboxes drown in the same repeated questions, and product, policy and catalogue answers live in documents no one can search in plain language. Assistants change that only when they answer from your content, not from a generic model.
We build the answer surface on your actual content — catalogue, docs, policies and FAQs — with a retrieval pipeline (embeddings + search), citations for every claim, guardrails for out-of-scope questions and a clean handover to a human with full context. We measure deflection and answer quality from day one.
- Kufanya kazi pamoja
- Kiongozi wa uwasilishaji mwenye jina + timu
- Wakati
- Prototype in 3–4 weeks; FAQ rollout scoped after
Tunachowasilisha
Mkazo kwenye sahihi.
- Commerce and support Q&A over your data
- Retrieval (RAG) pipeline over catalogue, docs and FAQs
- Guardrails, citations and human-escalation states
- Usage analytics and deflection measurement
Unachochukua
Kitu unachoweza kuendesha.
- Conversation and knowledge map
- Working assistant on your content with sources
- Guardrails, handover and admin controls
- Rollout plan, docs and measurement
Chunguza mwingiliano
Angalia mtiririko ukifunguka.
Maonyesho ya kiolesura kinachofanya kazi na data ya sampuli. Chagua kazi, fuatilia maendeleo na hakiki matokeo yaliyopendekezwa.
See the system
think in steps.
Choose a workflow, inspect the sample input and review the proposed output. You make the final call.
Find inconsistencies in a small sample product catalogue.
Product: Wireless headphones · Category: Audio · Compatibility: missing · Related products use the Headphones category.
- 01Inspect sample product fields
- 02Compare naming and categories
- 03Prepare suggested corrections
Your review workspace.
Run the example to reveal the proposed changes.
This browser simulation demonstrates the workflow and interface. Its sample responses are predefined; it does not call an AI model, access a store or publish changes.
Kabla hatujaanza
Uwazi kidogo
huenda mbali.
01Mnahitaji nini kutoka kwetu kuanza?
Maelezo mafupi ya tatizo, kiungo cha tovuti au chombo cha sasa ikiwa kipo, na matokeo muhimu yangekuwaje. Huhitaji vipimo vilivyokamilika. Ufikiaji, DPA/NDA na mahitaji ya maudhui tunakubaliana wigo ukiwa wazi.
02Mnaweza kufanya kazi na tulichonacho?
Ndiyo. Tunaanza na usanidi na mipaka yenu. Uboreshaji makini au muunganisho unaweza kushinda ujenzi upya — tutaeleza chaguzi na masharti, na gharama, kabla hamjaahidi.
03Gharama, wakati na SLA hukubaliwaje?
Baada ya ugunduzi, pendekezo lililo wazi: matokeo, hatua, ratiba, msaada na masharti ya SLA. Kuanza kwa sahihi; kila badiliko hufafanuliwa upya kwa maandishi kabla ya kazi ya ziada.
Utaalamu unaohusiana