Intelligent Automation
Combines RPA machine learning and rules engines to automate end-to-end business processes that involve documents decisions and multiple systems so work moves through without manual handoffs.
Everything included under this practice line.
Process discovery using task mining and interviews to map what actually happens versus what the SOP says
Document understanding for invoices contracts forms and IDs with structured extraction and confidence scoring
Decision automation using business rules engines and predictive models with human review on low-confidence cases
RPA bots for UI-driven legacy systems where APIs do not exist
Orchestration across bots APIs and human tasks with SLA tracking and exception routing
Straight-through processing metrics and continuous tuning of confidence thresholds
Bot health monitoring credential rotation and change resilience when target apps update
The stack we reach for.
What the business gets, measured.
- Straight-through processing rates that reduce manual touchpoints on high-volume work
- Lower unit cost on document-heavy operations like accounts payable claims and onboarding
- Fewer errors and rework on data entry between systems
- Faster cycle times on customer-facing processes
- Freed capacity for staff to handle exceptions and judgment work
The specialists behind this practice line.
Process analysts and RPA developers work with the business owners of each process to map the current state and identify the automation candidates. Machine learning engineers handle the document extraction and decision models where deterministic rules are not enough.
Compose several capabilities into one engagement.
Generative AI Solutions
We build production GenAI features on top of Claude GPT-4 and open-weight models. Text image and code generation wired into your product with proper eval loops and cost controls.
AI Agents & Workflow Automation
Multi-step agents that call tools hit your APIs and finish real work. Built with LangGraph or Anthropic's agent SDK with human-in-the-loop checkpoints where the blast radius is real.
LLM Integration
We wire LLMs into existing apps behind a stable API. Provider routing across Anthropic OpenAI Bedrock and self-hosted models so you can swap without rewriting callers.
AI Chatbots & Virtual Assistants
Support and internal-ops bots grounded in your docs and ticket history. Deployed to web Slack Teams or WhatsApp with escalation to a human when confidence drops.
Retrieval-Augmented Generation (RAG)
RAG pipelines over your PDFs wikis and databases. Chunking hybrid search and reranking tuned on your actual queries not a demo dataset.
MLOps
The plumbing that keeps models alive in production. Training pipelines model registries feature stores and monitoring for drift and quality regressions on real traffic.
AI-Powered Business Applications
Full applications where AI is the core feature not a sidebar. Copilots for sales ops finance and legal built on your data with role-based access and audit trails.
Let's talk
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