Enterprise AI that works inside your business and earns its keep

Stackera designs, builds, secures, and operates AI products grounded in your data, connected to your workflows, and measured against real business outcomes.

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From context to action.

Permission-aware. Evaluated. Human-controlled.

What's happening in Enterprise AI

The hard part is no longer generating an impressive response. It is operating AI reliably across real systems, permissions, policies, and changing business conditions.

From copilots to operations

Teams now expect AI to use business context, call approved tools, and know when to hand control back to a person.

Governance is the architecture

Permissions, traceability, and human oversight must be designed in before AI enters a high-value workflow.

Evaluation runs in production

Quality, compliance, and outcomes need continuous testing as models, workflows, and data change.

Agents are the new interface

Whole tasks—reconciliation, triage, reporting—are delegated to agents, with people reviewing instead of doing data entry.

Orchestration beats model access

Models are a commodity; the differentiator is how safely they connect to your data, permissions, and workflows.

Governed AI is table stakes

Customers, auditors, and regulators expect audit trails and human oversight in any AI-assisted process.

The problems businesses are facing

The gap between a compelling AI demo and a dependable business system appears in integration, trust, security, ownership, and measurable value.

Promising demos stall because nobody owns the path to production. Without secure integrations, an operating model, and a rollout plan, the pilot stays a side project while the business keeps waiting for value.

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Capabilities that turn models into dependable products

From generative AI and autonomous workflows to knowledge intelligence, Web3, and machine learning, we connect AI capabilities with the engineering and governance needed for production.

AI Development

Custom AI applications, secure integrations, and production engineering built around your business workflows

Generative AI and LLMs

Generative AI, LLMs, copilots, multimodal experiences, and fine-tuning for domain-specific tasks

Agentic AI and Workflow Automation

Tool-using agents and coordinated workflows with approvals, human handoffs, and recoverable execution

RAG and Knowledge Intelligence

Permission-aware retrieval, connected knowledge sources, and cited answers grounded in your enterprise data

AI-Powered Web3

On-chain intelligence, wallet analytics, and AI-assisted Web3 experiences connected to blockchain data

AI Consulting and Governance

AI strategy, use-case prioritization, readiness assessments, and governance with clear ownership and controls

Machine Learning and Data Intelligence

Predictive models, anomaly detection, and decision support built on reliable data pipelines and measurable outcomes

AI Analytics

Natural-language data exploration, automated insights, and intelligent dashboards that turn business metrics into actionable decisions

Platforms we deliver

Each platform begins with a defined operational job, the business context required to perform it, and controls proportionate to the decision.

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Support Intelligence

Grounded agents resolve payment, account, fee, and settlement questions with live transaction context and controlled escalation.

Payment status
Account context
Human escalation

Company Brain

A governed knowledge layer connects SOPs, quality records, shipment history, and supplier data to source-backed answers.

Approved SOPs
Source citations
Access controls

Data Insights

Natural-language analysis turns wallet, protocol, liquidity, and market activity into traceable on-chain intelligence.

Wallet intelligence
Liquidity signals
On-chain evidence

Analytics

AI correlates financial events, logs, metrics, and traces to explain failures, reconciliation gaps, and transaction health.

Transaction traces
Reconciliation
Service health

Alerts

Incident intelligence connects alerts to service ownership, recent releases, dependency health, and approved runbooks.

Release context
Dependencies
Runbooks

The right engagement for your next AI product

Start with a defined build, extend your team, or take an existing AI product into production. We agree the scope, success measures, and ownership before delivery begins.

Fixed-Scope Build

A focused AI assistant or workflow delivered against an agreed specification, evaluation criteria, and integration plan.

Best for: Teams launching a defined AI use case with a clear business outcome.

4–8 weeks

Dedicated Team

An embedded team that brings product, data, and security engineering into your AI roadmap and release cadence.

Best for: Organizations expanding AI across products and business workflows.

Team embedded in 3 days

AI Integration

Connect AI to your existing product, permissioned data, and business systems with evaluation and human review built in.

Best for: Teams adding intelligence to a product their customers already use.

Scoped

Existing AI Takeover

Take ownership of an existing AI application, review its retrieval and model behavior, and prioritize production improvements.

Best for: Teams inheriting an AI codebase or moving beyond an initial pilot.

Platform takeover in 3 days

How Delivery Runs

1 week
Discovery & Architecture
Define the workflow, data access, evaluation criteria, and system boundaries, then agree a delivery plan.
4–6 weeks
Build & Launch
Deliver working increments with source-grounded outputs, permission checks, and evaluations before release.
Ongoing
Operate & Improve
Monitor quality, cost, and user feedback. Maintain evaluations as models, data, and business requirements change.