AI integration services
You don't need a new platform to benefit from AI. You need intelligence added to the systems your team already lives in. We integrate AI into your existing products, CRMs, ERPs, and internal tools with minimal disruption.
4.9 / 5 client rating
19 verified client reviews
Agentic AI Market Report 2025–2029
Recognized among notable AI engineering vendors
ISO/IEC 27001:2022
Information security management certified
AWS · Google Cloud · Microsoft
Cloud technology partnerships
Our AI Integration services
AI features for your product
Search, summarization, generation, and assistant features designed and shipped inside your existing application.
CRM & ERP intelligence
Scoring, drafting, and data-hygiene AI embedded in Salesforce, HubSpot, and the systems of record you run today.
API & pipeline integration
Model providers wired into your backend with caching, fallbacks, cost controls, and observability from day one.
Legacy system enablement
AI capabilities layered onto older systems through APIs, middleware, or RPA where no integration path exists.
Security & compliance review
Data-flow mapping, PII handling, and access controls validated before anything touches production data.
What we build with it
In-app AI assistants
Your users get answers and actions inside your product, not in a separate tab.
Smart search
Semantic search over your product's content that understands intent, not just keywords.
Auto-drafting
Replies, notes, and summaries pre-written inside the tools where work happens.
Data enrichment
Records cleaned, deduplicated, and enriched continuously in the background.
Where this delivers the most
A six-step path from idea to production
Frame the problem
We start with your business goal, not the technology. Workshops with your team surface the workflows, bottlenecks, and metrics that matter.
Assess feasibility & ROI
Every candidate use case gets a feasibility check and a dollar figure: expected savings or revenue against build and run cost.
Prototype fast
A working proof of concept on your real data within weeks, so decisions are made on evidence instead of slideware.
Build for production
Security, permissions, monitoring, and human-in-the-loop controls are engineered in from the start, not bolted on later.
Integrate & launch
We connect the solution to the tools your team already uses, train your people, and launch with clear rollback plans.
Measure & improve
Post-launch, we track the metrics defined in step one and keep tuning (models, prompts, and workflows) as your business evolves.
The stack behind the work
Chosen per project for capability, cost, and your team's ability to own it later, never by vendor allegiance.
- Claude (Anthropic)
- GPT (OpenAI)
- Gemini
- Llama
- Mistral
- LangChain
- LlamaIndex
- Hugging Face
- PyTorch
- TensorFlow
Common questions
Related work
Post-trade reconciliation automation for a trading platform
A brokerage's operations team spent every morning manually reconciling trades across three systems. An automated pipeline with an exception-handling agent now clears the day's book before the team's first coffee.
Read case study
AI support assistant for a growing e-commerce brand
A D2C retailer's support queue doubled every holiday season. A grounded AI assistant now resolves the routine majority (order status, returns, product questions) and hands the rest to agents with full context.
Read case studyTell us about your project
We'll come back within one business day with an honest read on feasibility, approach, and cost.