Measurable Impact, Built For Scale
We design, build, and operate AI agents and RAG systems with guardrails, evaluations, and human‑in‑the‑loop so your team sees measurable impact, not just demos.
Generative AI Services
Challenges we solve
The common blockers we remove so teams can adopt AI safely and effectively
- Unclear use‑cases and value measurement
- Hallucinations and reliability concerns
- Security, privacy, and compliance risks
- Fragmented tools and data silos
- Difficulty moving from pilots to production
Our approach
A pragmatic, evaluation‑driven path from ideas to production systems
Discover
Clarify goals, risks, and success metrics. Identify highest‑value use cases and data readiness.
Design
Select models and patterns, define guardrails, and plan evaluations and human‑in‑the‑loop.
Build & Evaluate
Ship pilots with retrieval and tools, run evals, and iterate quickly with observability.
Operate
Deploy to production with monitoring, consent logging, and continuous improvement.
The agentic enterprise
AI Agents for Every Team
Knowledge Agents
Turn scattered institutional knowledge into instant answers — cutting search time and boosting productivity.
Sales Agents
Automate lead research, outreach, and routing so your team can close faster and focus on the right opportunities.
Marketing Agents
Launch, test, and optimise campaigns automatically while your team focuses on the big ideas, not briefing decks or A/B tests.
Engineering Agents
Agents that build alongside developers — scaffolding, refactoring, and integrating across tools to accelerate delivery.
Customer Service Agents
What took a queue and a human now takes seconds and an agent — they listen, understand, act, and escalate only when it matters.
Compliance Agents
Interpret policy, monitor risk, and flag anomalies in real time. Automate the overhead without compromising control.
Curious what this looks like live? See how Beacon Finance tripled qualified demos →
Our stack
Technologies we build with
Open‑ and closed‑weight models, retrieval, vector stores, orchestration, and MLOps — selected to fit your security, latency, and cost goals.
Our agents are
RAG Answers with Citations
Verifiable answers from your sources; citations included.
- Use RAG to deliver accurate, verifiable answers
- Search across PDFs, wikis, contracts, and more
- Reduce hallucinations and build user trust
Secure Actionable Agents
Secure tool use with consent logs and fallbacks.
- Connect to tools and data sources via MCP
- Act on real‑time inputs in context
- Deliver value without changing your existing stack
Multi‑Agent Orchestration
Chain agents safely; measure end‑to‑end quality.
- Orchestrate complex tasks using A2A protocols
- Scale across teams, tools, and workflows
- Built for interoperability, resilience, and enterprise scale
Production‑ready patterns
Retrieval‑augmented generation with versioned prompts, evals, and feature‑flagged rollouts. SOC2‑friendly workflows and audit trails.
Full‑stack agent ops
Orchestrators, tools, vector stores, and observability. We trace every run and feed learnings back into models and UX.
Model‑agnostic delivery
OpenAI, Anthropic, Google, and open‑weights where it makes sense. We pick what fits your data, latency, and cost goals.
What this looks like in practice
- We map your highest‑value AI workflows in a 45‑minute sprint.
- We pilot one use case first and define success metrics before scaling.
- We integrate with your existing tools, data, and model providers.
- We add human‑in‑the‑loop checkpoints for critical outputs.
Reassurance
- No long‑term contracts
- Pilot before rollout
- Works with existing tools
- Human‑in‑the‑loop by default
Ready when you are
Share your next growth target and we’ll map the AI rituals to support it.
We’ll respond within one business day with a tailored agenda, consent checklist, and a sample workflow to review together.