01DISCOVER
AI strategy
We find the processes where intelligence changes the economics and build a practical implementation roadmap.
Diagnostic · ROI model · Roadmap AI INTEGRATION / AI SYSTEMS FOR BUSINESS
Business,
thinking
faster.
We design AI systems that understand company context, do the work and keep critical decisions under human control.
SHOW ME:
SYSTEM ONLINEAI INTEGRATION CORE / 01
BUSINESSAICONTROLLED
INTELLIGENCE
DATA PEOPLE ACTIONS POLICYINTELLIGENCE
14:42:06Context synchronizedOK14:42:08Next action ready98%14:42:09Awaiting approvalHUMAN
10 daysto an AI opportunity map
4–6 weeksto a working pilot
1 metricfor every scenario
Human controlfor critical decisions
SENSE✦THINK✦ACT✦GUARD✦LEARN✦SCALE✦SENSE✦THINK✦ACT✦GUARD✦LEARN✦SCALE✦
/ WHAT WE BUILDNot a standalone bot.
Not a standalone bot.
A new way to work.
A strong AI project changes the entire path of work — from the incoming signal to a controlled outcome.
02BUILD
AI agents
We build digital operators that understand context, take action and know exactly when to bring in a person.
Sales · Service · Operations03KNOW
Enterprise Copilot
We connect documents, data and company expertise in one secure decision interface.
RAG · Knowledge graph · LLM04SCALE
Business AI layer
We orchestrate models, systems and teams so AI becomes a governed part of your infrastructure.
Agents · Evals · Governance/ AI OPERATING SYSTEMIntelligence
Intelligence
as a system.
The best AI solutions do not end with a model response. They see context, act in your tools, follow the rules and improve from real outcomes.
06connected
layers
layers
01SENSE
Sees the context
CRM, documents, calls, events and metrics form one current operating picture.
Data connectors02THINK
Understands the task
The model uses company knowledge, rules and the history of the specific process.
RAG · Models03ACT
Does the work
The agent creates documents, updates systems, runs workflows and coordinates steps.
Tools · Workflows04GUARD
Knows the boundaries
Roles, limits, approvals and audit trails protect data and decision quality.
Policy · Audit05LEARN
Improves quality
Evaluations, feedback and real outcomes create a continuous improvement loop.
Evals · Feedback06SCALE
Grows with the business
The architecture is not tied to one model and supports new teams, data and use cases.
API · Multi-model/ LIVE PRODUCT VIEWWe do not show magic.
We do not show magic.
We show control.
Every important step is visible: what AI understood, what it proposes, how confident it is and where a person is required.
ACTIVE MISSION / SALES / 0248
AWAITING HUMANHandle a new customer request
✓01 · INPUTRequest recognizedTelegram · 0.2 sec
✓02 · CONTEXTCRM record and history foundAccess rights verified
0303 · HUMAN APPROVALDecision preparedConfidence · 94%
0404 · ACTIONUpdate the opportunity and prepare a replyAwaiting approval
0505 · VERIFYVerify result and permissionsQueued
0606 · LEARNRecord the resultQueued
LIVE EVENT LOG
HUMAN_APPROVALpolicy passed
BITRIX24_UPDATEwrite success
OUTPUT_VERIFIEDno conflicts
METRIC_RECORDEDmission closed
CONFIDENCE94%
above the 87% threshold
HUMAN CHECKPOINTHThe account manager controls the decision
AI has prepared the action, while the critical decision remains under human control.
LIVE METRICS
PROGRESS64%
EVENTS2
HUMAN CONTROLWAIT
CONNECTED CONTEXT
SYSBitrix24SYNC
KBKnowledge baseVERIFIED
INTERACTIVE DEMO / SAFE SANDBOX
Switch the scenario and approve the action to see the complete decision cycle.
/ METRIC BEFORE MODELImpact
Impact
first.
Then AI.
Before development we agree which metric must change and what comparison will prove the result. A pilot ends with a decision, not a polished demo.
Our approach ↗AI INTEGRATION / VALUE CONTRACTMEASURABLE BY DESIGN
BASELINE
OBSERVEMeasure “before”
Speed, cost, quality or revenue in the current process.
TARGET
ALIGNChoose one metric
Do not hide the outcome behind dozens of technical indicators.
DECISION
PROVECompare on real data
Scale only what has proven business value.
✓NO DEMO
THEATRE
THEATRE
/ CASE LABBefore and after.
Before and after.
Measured.
Reference impact models for a pilot. Final targets are set after we analyze your process and data.
BEFORE25 minfirst-response time
TARGET MODEL / 01
Inbound requests
1Channel→2Context→3Qualification→4CRM✓
AI assembles the data and prepares the next action; the manager confirms commercial terms.
WITH AI< 2 minfirst-response time
Figures are demo targets, not a performance promise. The exact metric is defined during the diagnostic.
/ AI PROCESS DESIGNERDescribe the process.
Describe the process.
See the system.
One guided flow assesses the task and process readiness, then builds a personalized implementation map in your browser. No data is sent to external services.
LOCAL AI DIAGNOSTICSTEP 1 / 06
01 / PROCESS
What work would you like to accelerate?
One sentence is enough. Example: “Managers manually sort email requests and copy the details into CRM.”
/ REFERENCE SCENARIOSFrom incoming signal
From incoming signal
to outcome.
Three examples of a governed AI process: context, action sequence, target metric and a clear line of responsibility.
01INBOUND / SALES
Inbound-request AI agent
Unifies channels, clarifies the request, checks the data and prepares the next CRM action.
1Channels→2Context→3Decision→4CRM✓
< 2 minfirst-response target
02TEAM / KNOWLEDGE
Team Copilot
Finds the answer across enterprise sources, respects access rights and cites every fact.
1Question→2Knowledge→3Verify→4Answer✓
−35%search-time target
03OPS / CONTROL
AI process dispatcher
Detects a deviation, explains the cause, proposes an action and escalates ambiguity to a person.
1Event→2Analyze→3Action→4Control✓
24/7process observation
Targets are refined after process and data analysis. They are pilot hypotheses, not guaranteed results.
/ INTEGRATIONS & GOVERNANCEIn your environment.
Open Security Center ↗
In your environment.
Under your rules.
We do not force the business to replace its stack. We connect models, data and familiar tools with roles, audit logs and no single-provider lock-in.
OpenAIAnthropicGigaChatYandexGPT1CBitrix24amoCRMSAPMicrosoft 365Google WorkspaceTelegramREST API
01Role-based access
02Audit trail
03Human in the loop
04Multi-model architecture
/ PATH TO VALUEValidate quickly.
Validate quickly.
Scale with confidence.
Every phase ends with a concrete artifact and a decision: continue, adjust or stop without irreversible cost.
Diagnostic
We map the process, data and losses, compare use cases and select the one with the strongest potential.
Working pilot
We launch in a real operating environment, connect the required systems and validate the agreed business metric.
Scale
We strengthen security, reliability and coverage, train the team and expand the pattern to new processes.
/ BEFORE WE STARTShort.
Short.
Clear.
What teams usually need to understand before the first meeting and AI project.
01Which process should we start with?+
Start where repeatable knowledge work, a digital trail and a clear cost of delay or error meet. During the diagnostic we compare candidates and choose the strongest one.
02What if our data is not ready?+
That is a common starting point. We assess the sources and define the minimum preparation needed to get a result without a multi-year data program.
03How do you protect company data?+
Before development we define access rights, permitted actions, data location and control points. Actions are logged and risky decisions require human approval.
04Can we use different AI models?+
Yes. We select models for language, quality, speed, cost and security requirements. The architecture allows provider changes without rebuilding the whole solution.
05When will we see the first result?+
The diagnostic takes 10 business days. A working pilot usually takes 4–6 weeks, after which scaling is decided using the actual metric.
Your next
high-impact process
starts here.
In 45 minutes we will map the challenge, data and constraints — and identify where AI can create measurable value this quarter.
Book a conversation ↗