native ai crm · coworkers that never sleep

AI agents for business
inside one CRM. They work
while you sleep.

Ready-made digital coworkers in a single CRM: they sell, recruit, answer customers, run the calendar, analyse calls and extend the product itself. In 5 languages. 24/7.

2,400+ teams on DivaK for any command
03:47 · night shift
D
AI · sales
Diva sales
247 conversations
D
AI · recruiting
Diva recruiter
52 CVs
D
AI · support
Diva support
18 tickets
night shift · 23:00 → 07:00

While your office slept, we closed 11 deals, interviewed 4 candidates and answered 247 customers.

+11
deals closed
+58
leads handled
24
candidates screened
0
hours of overtime
23:14
Diva salesAnswered Beauty Lab on Telegram in 3 seconds. Sent the quote.
+1 proposal
23:38
Diva recruiterScreened 8 Senior Python CVs · 3 moved forward.
match ≥ 80%
00:12
Diva supportClosed 6 tickets without escalation. One handed to a human.
CSAT 4.9
01:04
Diva salesOrbita Health deal closed. $4,600.
+ won
01:47
Diva recruiterRan the technical interview with Alex T. Score 9.1/10.
recommends an offer
02:15
Diva receptionistRescheduled 4 bookings, sent reminders. 0 no-shows expected.
−64% no-show
02:47
Diva salesEscalated an approval to you: 18% discount (over the 15% cap).
waiting on you
03:22
Diva analystSpotted a −12% conversion drop on Avito. Root cause ready by morning.
analysis
03:47
Diva developerAdded an LTV field to the contact record. 12 tests green.
awaiting merge
04:10
Diva supportUpdated the knowledge base with 2 articles based on 5 similar tickets.
auto-learn
04:58
Diva salesNordic Home — deal Won. $2,000. Follow-up in 30 days.
+ won
05:31
Diva recruiterBooked the final with Alex T. for Thu 2pm. Link sent.
booked
06:20
Diva analystMorning digest ready. 5 insights. Top one: Avito converts 2× when we answer in under 60 seconds.
digest

A team of AI coworkers. One that never asks for time off.

Six roles out of the box. Each one comes with a name, a persona, channels, tools and limits. Rename them, retrain them, replace them.

D
AI · Sales representative
Carries the customer from the first hello to a signed contract. Answers in seconds, never drops a follow-up, closes deals on its own.
TelegramWhatsAppEmailSIPCRM
247/night
conversations
41%
conversion
D
AI · HR / Recruiter
Reads CVs, runs screening, calls candidates and conducts technical interviews with code and cases. Matches calendars. Joins the call with a recording.
LinkedInTelegramGoogle MeetCalendarEmail
52/day
CVs reviewed
×6
hiring speed
D
AI · Support
Closes 82% of tickets without escalation. Knows your product, the customer's history and their mood. Knows when to call a human.
TelegramWhatsAppEmailWeb ChatKnowledge base
82%
resolved without humans
4.8/5
csat
D
AI · Analyst / BI
Listens to calls, reads conversations, scores sentiment, builds reports. In the morning: a digest of what grew, what fell, why, and who to contact.
SIP transcriptsSheetsReportsSlack
38min
per report/month
+22%
more insights
D
AI · Reception / booking
Finds a time, books the slot, sends the confirmation, reminds the day before, reschedules when the customer runs late. Never forgets to call.
Google CalendarBooking systemsSMSTelegram
−64%
no-show
24/7
no breaks
D
AI · CRM developer
When you need a new field, report, stage or automation — just say so. It shows a diff, runs the tests and ships. One click to roll back.
SchemaAutomationsSessionsGit · auto-diff
12min
per task
0
surprises in prod
Hire a coworker in 3 clicksHire in 3 clicks — and see what they can do.
flagship · recruiting without a recruiter

The AI hiring agent fills a role in a week, not a month.

It parses job boards, filters CVs, calls candidates, runs the technical interview, agrees a time, joins the final call and hands you a finished digest.

live · hiring right now
app.diva.ai / crm / hr / candidates · Senior Python · 14 open

New CVs18

Alex T.92
Senior Python
pythonawsteam-lead
Maria K.74
Senior QA
seleniumapi5 yrs
Dmitry L.
Senior Python
hotscan…
Elena P.
Middle Python
scan…

Screening by Diva recruiter7

Irina V.84
Senior Python
djangofastapikafka
Pavel R.78
Senior Python
mlpytorch

AI technical interview3

Anton S.88
Senior Python
interview 2/8

Final with you2

Sofia M.91
Senior Python
recommended
● CV analysis — in real timescanning
The Diva recruiter reads a candidate's CV and returns a verdict in 8 seconds.
87
Alex T., Senior Python
match · senior python · remote
Python · 7 years, Django + FastAPI+18
AWS, Kubernetes, CI/CD+12
2 years of team lead experience+6
Willing to relocate — OK+2
3 short stints in a row (<1 year each) — ask why
8-month gap in 2023 — worth asking about
Open-source activity: 2 repos with 400+ stars
● technical interview by the Diva recruiterlive · q4 of 8
It asks the questions, reads the code and scores the answer. You read the summary in the morning.
Diva recruiter · ai hr
Hi Alex! I'm the Diva AI recruiter. This isn't a scripted bot — I'll ask by voice, but we can do it in chat if you prefer. Ready?
Chat works for me.
question 3 / 8
Write a retry decorator that retries a function on exception, with exponential backoff and at most 5 attempts.
Sure, one moment.
def retry(max_attempts=5, base=0.5): def deco(fn): @wraps(fn) def inner(*a, **kw): for i in range(max_attempts): try: return fn(*a, **kw) except Exception: if i == max_attempts-1: raise time.sleep(base * 2**i) return inner return deco
diva recruiter · score
Clean solution. Correct backoff, preserved the function via wraps. Missing jitter and error logging — but solid fundamentals at senior level, 9/10.● score 9.1 / 10
● calendar matchingauto-match
It sees your slots and the candidate's. Proposes. Books. Reschedules.
montuewedthufri
10:00
11:00
14:00
15:00
16:00
Diva recruiter proposesBookedYour calendar
“Alex, does Thursday 2pm work? The Meet link goes out 10 minutes before. If you need to move it, I'll find a new slot myself.”
● joining the call + recordinglive · recording
The Diva recruiter is on the call. Records. Transcribes. Highlights what to ask next.
Meet · Final with Alex T.
rec · 12:47
A
D
T
Alex:…why I left the last one — the whole team changed after the rebrand and the project was frozen.
HINT → YOU
“Good answer, honest. Now ask about queue experience — Kafka was on the CV but didn't come up in the example.”
the magic · building agents with words

A no-code AI agent builder. Describe it — Diva builds the team.

No prompt engineering. No JSON. Say “I want a support team of 3 agents” and you get 3 agents with tools, channels and rules. Edits work the same way.

diva · in plain language
Build a sales team for a clinic. I need a receptionist (Telegram + SIP), a sales rep (Avito + WhatsApp), and an analyst that tracks conversion and messages me in the morning.
Got it. I'll create 3 agents. Receptionist — with calendar and booking tools. Sales rep — an AI sales script and approval for discounts > 10%. Analyst — a daily digest on Telegram at 9:00. Privacy rules: add them?
Yes. Never book a meeting without my approval if the customer has a red flag. Never promise more than 15% off. No WhatsApp messages after 10pm. And every refund goes through me.
Recorded 4 rules. Checked them against existing deals — 0 conflicts. Launch?
Say something else:
→ 3 agents created · 4 rules · 0 conflicts
Your new team
D
Diva receptionist · AI reception
Reception · telegram · sip
Google CalendarBooking
D
Diva sales · AI sales
Sales rep · avito · whatsapp
AI scriptapprove cap 10%
D
Diva analyst · AI analyst
Reports · daily digest
SheetsTelegram · 9:00
guardrails · only with your permission
Never book a meeting if the customer has a red flag — only through you
Never promise more than 15% off — escalate for approval
No WhatsApp after 10pm — hold until morning
Refunds go through you. Never on its own
Any action over $600 — with a preview and confirmation
sales · a live example

The AI sales agent never loses a lead. Ever.

Every deal comes with a summary, a next step and a list of risks. It updates in real time while the conversations are happening.

Diva sales · live
app.diva.ai / crm / deals · Diva sales · AI rep
K

Discovery6

Stomus Clinic
Diva sales summarised the call and moved it to Proposal.
2,000Diva sales
Nordic Home
Imported from Avito — Diva sales messaged on WhatsApp.
1,020human
LoftRent Moscow
Lead quality 82% — hot.
2,650Diva sales

Proposal4

Beauty Lab · chain
Diva sales is waiting on approval for a 12% discount.
19,800Diva sales
Zentera CRM
4 objections handled on Telegram.
6,200Diva sales
DentaPro
Meeting on Friday at 2pm.
3,500human

Won11

Orbita Health
Closed by the agent — no human rep involved.
4,600✓ closed
Solstice Group
NPS 9, follow-up in 30 days.
8,600✓ closed
record
Beauty Lab
DEAL-2841
● Diva sales is writing
Beauty Lab · a chain of 6 salons

The customer is interested in a corporate subscription. Main objection: price. Decision maker: the marketing director. Competitor: a rival booking suite. Sentiment: +0.42.

● next step
  • Send the Orbita case study — +31% conversion
  • Propose a pilot at 2 locations (12% discount)
  • Book a demo with an engineer for Thursday
● risks
Silent for 5 daysHIGH
Competitor mentioned twiceMED
Decision maker changingLOW
Ask about this deal:
and more · limited only by imagination

AI agents for any job. The limit is your imagination.

Build, experiment, invent — any digital coworker for your task. Same core, different data and rules. In words, in 5 minutes.

Customer support

Autonomous L1, escalation to L2 by confidence. The knowledge base updates itself.

82% of tickets without humansmultilingual chatJira / Linear auto-issue

Quality assurance

Listens to 100% of calls and chats. Scores them, finds script violations, writes coaching feedback.

0 missedscript complianceNPS forecast

Marketing

A/B tests offers in campaigns, writes posts, generates landing pages per campaign, tracks ROAS by source.

email / push / telegramSEO contentUTM analytics

Back office

Closes paperwork, reconciles records, sends invoices, handles correspondence with counterparties. Within the limits you set.

accounting systemselectronic document flowemail

Finance

Tracks cash flow, forecasts the balance, spots discrepancies, and answers the owner's “what am I worth right now”.

bank integrationsdaily financial reportanomalies

Training / Onboarding

Walks new hires through their first weeks: teaches, tests, gives feedback. Customers too.

video plan + quizzesprogress tracking24/7 chat
integrations · plugs into your stack

Integrations with amoCRM, Bitrix24 and 1C — and 1000+ more services you already use.

Channels, CRMs, calendars, payments, telephony, spreadsheets. Missing one? The Diva developer adds it over the API in minutes.

1000+

Ready-made connectors to the world's most popular services — out of the box, without an integrator.

TelegramWhatsAppAvitoamoCRMBitrix241CGoogle CalendarNotionSlackJiraStripeYClientsVKHubSpotSalesforceMoySkladSIP telephony+ 980 more
case studies · diva in production

AI agent case studies

Real deployments in support, sales and logistics — with numbers.

marketplace analytics

MPStats support on a 35-million-word knowledge base

We automated support over a huge knowledge base with zero model hallucinations. Billing is per resolved user question — for the outcome, not the tokens. Plus voice support agents over telephony.

0%
model hallucinations
35M
words in the knowledge base
water delivery

8 support flows on the Diva engine

Order intake and processing, tracking, repeat and cancellation, corporate customers, voice agents. The previous implementation could not hold a flow — it looped, skipped confirmation and payment, and invented prices. We moved it to the Diva flow engine: frame gates hold each step and guards stop the agent inventing actions.

94.9%
reference suite passing
10 → 0
defect classes
transport · freight forwarding · usa

Digital coworkers for a logistics company

Integrations, languages and coverage — the details will appear here once the customer has signed them off.

soon
case metric
time to deploy
deployment · 12 stages

How AI agents get deployed into a business.

A systematic, safe and measurable path — from diagnosis to optimisation inside the working business.

Phase 1

Preparation

We map the processes and put the knowledge in order.

  • 01
    Customer diagnosisCore value, channels, products, SLAs, KPIs, process owners.
  • 02
    Knowledge gatheringWebsite, CRM, knowledge base, Drive, Wiki, files, email.
  • 03
    Knowledge reviewWe strip out stale content, duplicates and conflicts.
Phase 2

Design

We assemble the structure, the flows and the agent's rules.

  • 04
    Building the structureKnowledge tree: sales, support, logistics.
  • 05
    Building the flowsConversation funnels — from greeting to close.
  • 06
    AI configurationPrompts, roles, limits, escalations, access.
Phase 3

Launch

We connect the systems and test on live conversations.

  • 07
    IntegrationsCRM, ERP, telephony, messengers, help desk.
  • 08
    TestingHundreds of conversations on a test rig, error review.
  • 09
    PilotLive traffic in steps: 10% → 20% → 50% → 100%.
Phase 4

Operation

We hand it to the team and keep improving it.

  • 10
    Team trainingHow to configure, supervise and read the dashboard.
  • 11
    Production launchOperators, channels and customers — the agent is live.
  • 12
    OptimisationThe AI surfaces bottlenecks and growth opportunities.
sdk · for developers

An AI agent in production — in one npm i.

A thin typed client: describe the agent, call run(), get an answer. The agent loop itself runs on our servers.

The problems that usually cost teams weeks are handled out of the box:

Enterprise RAG, ready-made

A tuned knowledge base out of the box: retrieval, ranking, hallucination guards. No RAG pipeline to assemble by hand.

A flow engine

The best conversational flow engine on the market. Frame gates hold each step: the agent will not skip confirmation or payment, and will not loop.

The engine runs on our servers

The agent loop, memory and guards run with us. It scales without you, and the engine is never downloaded to the client.

Billing per outcome

Metering and billing are built into the gateway. You can charge per resolved customer question rather than per token.

Two clicks to a product

SDK plus a visual builder: test a hypothesis and get a working agent in a couple of clicks.

1 · your process

The SDK and your tools

A thin client and your own tool().execute — with your database and your secrets. Tool code and keys never leave your machine.

2 · diva gateway

Auth and metering

One sk-diva key: authentication, billing, routing and tenant isolation. A single egress that is easy to audit.

3 · diva engine

The agent loop itself

Model calls, tool orchestration, memory, RAG, compaction, sub-agents, guards and flow. The engine is never downloaded to you.

tools and secrets stay with you · the engine runs on our servers · the engine is never downloaded
When the model needs your tool, the run is parked: the engine asks your process to make the call locally. Only the result leaves your machine — the engine sees the tool schema and the model call, never your code.

The same task — four ways

A support agent with two tools and one hard rule: never refund more than $200 — escalate instead. Switch frameworks on the right — both sides are shown in full and the code scrolls.

Diva SDKLangGraph
import { Agent, tool, guard, z } from "@diva-ai/sdk";

const lookupOrder = tool({
  name: "lookup_order",
  inputSchema: z.object({ orderId: z.string() }),
  execute: ({ orderId }) => billing.getOrder(orderId),
});

const issueRefund = tool({
  name: "issue_refund",
  inputSchema: z.object({ orderId: z.string(), amountUsd: z.number() }),
  execute: ({ orderId, amountUsd }) => billing.refund(orderId, amountUsd),
});

const agent = new Agent({
  instructions: "You are a support agent. Look up the order first.",
  tools: [lookupOrder, issueRefund],
  // the hard rule — one declarative line
  guards: [guard.tool("issue_refund", { when: (i) => i.amountUsd > 200 })],
});

const { text } = await agent.run("Customer 4512 is asking for a $250 refund.");
import { ChatOpenAI } from "@langchain/openai";
import { tool } from "@langchain/core/tools";
import { createReactAgent } from "@langchain/langgraph/prebuilt";
import { z } from "zod";
// + your own OPENAI_API_KEY

const REFUND_CAP = 200;

const lookupOrder = tool(
  async ({ orderId }) => JSON.stringify(await billing.getOrder(orderId)),
  { name: "lookup_order", schema: z.object({ orderId: z.string() }) },
);

const issueRefund = tool(
  async ({ orderId, amountUsd }) => {
    // the rule has to be written imperatively INSIDE the tool
    if (amountUsd > REFUND_CAP) {
      return "BLOCKED: over $200 — needs escalation.";
    }
    return JSON.stringify(await billing.refund(orderId, amountUsd));
  },
  {
    name: "issue_refund",
    schema: z.object({ orderId: z.string(), amountUsd: z.number() }),
  },
);

const agent = createReactAgent({
  llm: new ChatOpenAI({
    model: "gpt-4o-mini",
    apiKey: process.env.OPENAI_API_KEY,
  }),
  tools: [lookupOrder, issueRefund],
  stateModifier:
    "You are a support agent. Never refund over $200 — escalate instead.",
});

const res = await agent.invoke({
  messages: [
    { role: "user", content: "Customer 4512 is asking for a $250 refund." },
  ],
});
Diva SDK · 22 lines
LangGraph · 42 lines
↕ the code scrolls — both sides are shown in full
what production actually needs
Diva SDK
LangGraph
CrewAI
Raw OpenAI
Setup
1 package + 1 key
4 packages + a key
pip + a key
package + your own loop
Provider keys
not needed
your own key
your own key
your own key
Choosing model and provider
not needed, the API decides
you pick the model
you pick the model
you pick the model
A hard business rule
declarative guard
an if inside the tool
an if inside the tool
an if in the dispatcher
A separate policy layer
guards / flow
smeared across the code
smeared across the code
smeared across the code
Agent loop and scaling
on our servers
in your process
in your process
in your process
Metering and billing
built into the gateway
you build it
you build it
you build it
Secrets and tool code
stay with you (park/resume)
with you
with you
with you
Streaming
agent.stream()
supported
limited
you assemble it

What changes after deploying AI agents.

Averaged across 2,400+ teams on Diva during 2025.

41%
conversion lift

An answer to the customer in 3 seconds. Never without a follow-up.

×6
team speed

4 hours of routine → 40 minutes. People on what matters.

24/7
no breaks, no holidays

Nights, weekends, public holidays — they work.

3 min
to your first coworker

No code. No integrator. Just plain language.

Questions about AI agents you are already asking.

What if an AI coworker does something stupid?

You set the rules for each agent yourself: “never promise more than 15% off”, “never book a meeting without my approval”, “no messages after 10pm”. Important actions happen only with your permission. Sessions record every step, and rollback is one click.

No. A new field, report, stage, automation or a whole new agent — all in plain words. The Diva developer agent writes the code, shows a diff and runs the tests.

We bill agent actions, not seats. For a mid-sized business it starts at 9,900 ₽ per month, including unlimited agents and channels. It usually pays for itself within 2–3 weeks on a single role.

In your region. Enterprise runs in a VPC or on-premise. Models are not trained on your data.

Yes. The Diva developer maps the fields itself and suggests schema improvements. No downtime, with a dry run on a copy first.

The first agent answers customers 15 minutes after signup. A full team of 6 roles takes 1–3 days including integrations.

get started

Give your team
AI coworkers
that never sleep.

Three minutes and Diva sales is answering customers, Diva recruiter is filtering CVs and Diva support is closing tickets. No card. No integrator.