Secure LLM Integration for Enterprise Systems
GPT-4o, Google Gemini, Claude, Microsoft Copilot, Perplexity, or Custom Models — securely integrated into your workflows.
іTurn LLMs into measurable business outcomes with secure pipelines, prompt engineering, and structured domain knowledge (RAG). Built for regulated environments, real users, and production SLAs.
Run It in Your Environment Privately
Controlled User Access (RBAC + SSO)
Audit-Ready Logs System
Built-In Data Protection
Flexible LLM Model Choice
Secure LLM Integration Services by devPulse
Organizations are under increasing pressure to adopt AI, yet generic chat interfaces rarely fit real enterprise workflows. Security and legal teams require clear data boundaries and auditability, product teams need consistent outputs, operations depend on predictable performance and cost control, and users expect AI to work inside the tools they already use.
devPulse integrates large language models directly into your existing systems with security, governance, and reliability built in. Our teams combine engineering, cloud, and applied AI expertise to deliver end-to-end LLM integrations — including secure data access, guardrails, monitoring, and cost governance — ensuring compliant, dependable AI that scales with your business.
What We Integrate
We integrate the right LLM for your requirements — and keep you vendor-independent.
We select and integrate the language model that best fits your compliance constraints, budget, and performance expectations, while designing the system architecture to support future model switching without disruption.
Each integration is treated as a replaceable system component, not a hard dependency.
OpenAI (GPT-4o)
High-quality, multimodal workflows for advanced reasoning, vision, and user-facing AI experiences.
Google Gemini
Optimized for Google ecosystem alignment, productivity integrations, and scalable cloud-native deployments.
Claude
Designed for long-context processing and structured reasoning in document-heavy and analytical workflows.
Microsoft Copilot / Azure OpenAI
Enterprise-grade deployments with governance, identity integration, and compliance alignment.
Perplexity
Best suited for research-driven, source-aware, and citation-focused AI experiences.
Custom & Open-Source Models
Fine-tuned, private, or self-hosted models for maximum control, data isolation, and cost optimization.
OUTCOME
Your product depends on capabilities and architecture, not a single AI vendor.
Responsible AI made simple and actionable. Transform your AI strategy today.
We typically integrate across
AI Chatbots
Telegram, WhatsApp, Facebook Messenger, and Slack, e-commerce platforms (Shopify) etc.
Docs
Confluence, SharePoint, Google Drive, Dropbox, Notion, file shares
Ticketing
Jira, Zendesk, Freshdesk, ServiceNow
Dev tools
Git repositories, CI/CD docs, wikis
Databases / APIs
SQL, data warehouses, internal APIs
Security reassurance
Access control is enforced end-to-end, so the model can’t see content the user can’t access.
our case study
Development of AI-Assisted Contract Review Platform
We built an AI-powered contract review system that standardizes clause checks, flags missing or risky terms, and accelerates redlining and approvals.
Key Features:
- 30% of contracts were processed with zero lawyer touch
- Approximately 3 FTEs were redeployed to M&A work
- Cycle time dropped by 60% to 80% (down to 2 days)
Where Secure LLMs Deliver Immediate Value
Practical AI use cases designed for regulated environments and embedded directly into your existing workflows — improving speed, consistency, and decision-making without compromising control or compliance.
- AI agent that drafts replies, suggests resolution steps, and links to internal policies
- Faster ticket triage and reduced escalations
- Consistent tone and compliance-aligned responses
- Contract Q&A with citations, clause extraction, risk flags
- Policy assistant for internal teams
- Template-driven outputs (structured summaries, redline guidance)
- Proposal drafts grounded in your playbooks and past wins
- Policy assistant for internal teams
- Customer-friendly explanations using approved positioning
- Internal assistant across runbooks, incidents, specs, and architecture docs
- Faster onboarding and fewer repeated questions
- Better reliability with traceable sources
How It Works With Us
Discovery Call
30–45 min with an architect and delivery lead to align on goals, constraints, stakeholders, and success criteria.
- Discovery notes + next-step plan
Solution Brief
Executive-ready scope covering milestones, risks, timeline, architecture (if needed), and KPIs.
- Solution Brief (PDF/Confluence) + implementation plan
Commercial Agreement
Define engagement model, team setup, pricing, timeline, and change process.
- SOW / proposal + delivery schedule
Proof of Concept
Validate feasibility, integrations, and performance with real stakeholder feedback.
- Working POC + learnings + refined plan
MVP
Build and launch a production-grade MVP with core features, QA, and monitoring.
- MVP in production + documentation + handover
Production Scale
Harden performance and security, improve UX, and optimize reliability and costs.
- Full-feature product release + roadmap
Support & Continuous Improvement
Ongoing maintenance, SLAs, and iterative enhancements with a dedicated team option.
- Support plan + monthly improvement cycle
Need expert guidance to turn LLM capabilities into reliable production systems?
Why Order From Us
Clear milestones and deliverables from MVP to production and scale, supported by transparent documentation and handover, flexible engagement models (fixed-scope pilot or dedicated team), and an optional support plan covering SLAs, monitoring, security reviews, and continuous improvements.
Why We’re the Best AI company
Most vendors can build a prototype. Fewer can take responsibility for a production system that real teams depend on. We’ve been doing exactly that since 2014 — for companies where reliability, security, and predictable delivery matter.
What you get with us:
Enterprise-first delivery DNA
Our portfolio is built around enterprise clients, with real governance, reviews, and production constraints.
Accountability you can insure
We maintain professional liability insurance, so risk management isn’t just a promise — it’s part of how we operate.
Long-term mindset
We design solutions that are maintainable, testable, and ready for scale — not one-off builds.
Low team attrition
You don’t lose context every few months. Your product knowledge stays in the team, which improves velocity and quality.
RESULTS
Fewer delivery surprises, smoother approvals, and a team that stays with you long enough to create compounding value.
our case study
Automating Lead Qualification with AI-Powered Real Estate Agents
Our team built an AI-powered lead qualification system for a large real estate investment firm, automating their leasing funnel and integrating directly with their CRM.
Key Features:
- 12% reduction in fraudulent applications
- 30 hours saved per broker, per week
- 100% uptime during CRM integration
faq
"ROI appears when AI becomes a workflow, not a feature. "
Most companies over-focus on “which model is best” and under-invest in governance, knowledge quality, and permissions. The fastest path to reliable enterprise AI is a controlled integration layer, measurable evaluation, and strict access enforcement — so AI becomes operational, auditable, and safe to scale.
— Anna Tukhtarova | CTO, DevPulse
Need a clear path from LLM idea to production?
Schedule a discovery session with devPulse.
