Agents
Delegate the work, keep the judgement.
Agents that read your sources, use your tools, and show their work — so your team reviews decisions instead of assembling context.
Agents
7 activeToday
Support triage — inbox #general
Retrieving·38 tickets
Vendor MSA review — Nordwind
Comparing clauses·64 clauses
RFP security questionnaire
Drafting gaps·112 / 118
Weekly engineering digest
Complete·5 themes
This week
Onboarding FAQ refresh
42 answers updated
Contract renewal watchlist
9 accounts flagged
Help-centre gap analysis
17 missing articles
Meet your team where they work
The same agents, the same knowledge, wherever the question is asked.
Web app
A workspace for chat, sources, agents and evaluation in one place.
import { Ragenta } from "ragenta"
const r = await agent.ask(
"refund window?"
)
API & SDK
Call an agent from your own product with a few lines of code.
Embedded widget
Drop a grounded assistant into your app or help centre.
Ragenta
Retention is 90 days on Team plans — see Security policy §4.
Slack & Teams
Answers in-thread, with the same citations and permissions.
It understands your organisation, not just your documents
Context, conventions and permissions carry into every run.
Contract terms
done · opus-4.5
Account history
running · gpt-5
Support tickets
running · gpt-5
Billing records
queued · qwen3
Parallel subagents
A broad question fans out across subagents, each answering one part and streaming findings back as it finishes.
“What did we commit to Nordwind on pricing?”
Knowledge with provenance
Every passage carries its source, its permissions and its freshness — so an answer can be audited, not just read.
Never quote an unapproved price
all agents
Cite the contract, not the summary
legal, sales
Escalate below 0.8 groundedness
support
Reply in the customer's language
support
Rules your team writes once
Tone, mandatory disclaimers, forbidden sources, escalation thresholds — written once and applied to every future run.
The whole loop, in one system
Ingest, retrieve, evaluate — and the evaluation feeds back into the first two.
Parse — layout-aware, tables preserved
Chunk — on structure, not character count
Embed — multilingual, one vector space
Sync — incremental, permissions carried
Ingest
Connect a source and Ragenta parses layout, chunks on structure, embeds and keeps it in sync — with the source's permissions attached.
Retrieve
Vector similarity and keyword matching run together, then a reranker orders what actually reaches the model's context.
score 30 reference questions
→ groundedness 0.94 (+0.06)
check citation coverage
→ 98% of claims linked
diff against last configuration
→ 2 answers changed
Evaluate
Groundedness, citation coverage and retrieval hit rate are scored on every change, so a regression surfaces before a user reports it.
What an agent can actually do
Read, act, and leave a trail you can follow.
$ retrieving across 4 sources…
reranked 38 → 6 passages
$ sql: revenue by region, last 4 quarters
answer drafted · 9 claims · 9 citations
Run tools, not just prompts
Query a warehouse, call an internal API, run Python in a sandbox, search the web — with credentials held server-side and never shown to the model.
Point at exactly what matters
Mention a document, a folder, a connector or a saved filter inline, and the agent scopes its retrieval to it for that run.
Knowledge base re-indexed
24 Aug · 09:12
Reranker enabled
24 Aug · 11:40
Model switched to opus-4.5
25 Aug · 08:05
Current configuration
26 Aug · 14:22
Every run is reproducible
Model, prompt, retrieved passages and tool outputs are versioned together, so any answer can be replayed exactly as it was produced.
Extend it without forking it
Connectors, skills and your own tools — all first-class.
Connectors
Managed sync for the systems your knowledge already lives in, with each source's permissions carried through to retrieval.
/support-reply
Draft a support reply grounded in policy
/contract-diff
Compare a contract against the playbook
/rfp-answer
Answer a security questionnaire from prior answers
/weekly-digest
Summarise a week of engineering activity
/clause-search
Find every document that mentions a clause
Agent Skills
Turn a prompt that works into a named, versioned skill with its sources, tools and output format fixed — then let the whole workspace run it.
Your own tools
Attach any Model Context Protocol server, or register a plain HTTP tool, and it appears to your agents alongside the built-in ones.
From the teams running it every day
“We had three separate search tools and none of them could answer a question. Ragenta replaced all three in a month, and the citations are the reason people actually trust it.”
Head of Operations
Logistics, 900 staff
“Support deflection went from a slide in a strategy deck to a number on a dashboard. The retrieval trace is what let us debug it ourselves instead of filing tickets.”
Customer Support Lead
B2B SaaS
“Permission-aware retrieval was the whole deal for us. Legal would not sign off on anything that indexed HR files into one bucket.”
IT Director
Financial services
“Our documentation is half Vietnamese, half English. One index handles both and an English question still finds the Vietnamese paragraph.”
Engineering Manager
Fintech, Ho Chi Minh City
“The agent does not just retrieve — it decides what to look up next. Watching it re-query after a weak first result was the moment this clicked for the team.”
Head of Data
Healthcare group
“We swapped the underlying model twice in a quarter without touching a single prompt. That flexibility is worth more than any single model benchmark.”
Principal Engineer
Enterprise software