AI as a serious engineering discipline.
Evaluation, guardrails, observability, and hands-on delivery from day one. We start with a Readiness Assessment, ship to production, and treat the system as software that has to be operated, not a demonstration to be shown.
Two ways most engagements begin.
Both are scoped clearly and led by the same partners from the first conversation through to operations.
AI Readiness Assessment
A scoped engagement that maps where AI creates value in your business, and where it does not. You leave with an executive scorecard, an ROI roadmap, and the three highest-value agentic opportunities prioritized for your business.
- Executive readiness scorecard
- ROI roadmap with sequencing
- 3 prioritized agent use cases
- Architecture and risk review
Agentic AI / Custom Agents
Multi-agent orchestration integrated with your CRM, ERP, and collaboration tools, with evaluation, guardrails, and observability built in from the start.
Full capability grid
RAG & Knowledge Bases
Vector databases, embedding strategy, and hybrid search architectures that turn enterprise knowledge into reliable, secure retrieval.
AI Integrations
Bring large language models into Salesforce, HubSpot, Zendesk, and internal tooling without disrupting the systems your team already relies on.
AI Consulting & Strategy
Strategic guidance on where AI creates value, where it does not, and how to sequence investments so pilots reach production.
Prompt Engineering & Evals
Evaluation harnesses, regression testing, and prompt libraries that keep AI features performing reliably as they scale.
What teams put into production.
Real applications across customer experience, operations, product, and data, drawn directly from engagements we have delivered.
Intelligent Chatbots
Conversational agents that understand context, hand off to people gracefully, and improve with every real customer interaction.
Personalized Recommendations
Product, content, and next-action recommendations tailored to the user, designed to lift conversion and improve long-term retention.
Sentiment Analysis
Customer feedback, reviews, and social signals classified continuously, with alerting when sentiment moves in either direction.
Document Processing
Extraction, classification, and routing of invoices, contracts, and claims, with human review at the steps that warrant it.
Predictive Maintenance
Failure prediction drawn from sensor and operational data, designed to reduce downtime and the unplanned spend that follows it.
Workflow Automation
Agents that execute multi-step internal workflows across the systems your team already relies on every day.
AI-Powered Search
Hybrid retrieval that understands intent and surfaces the answer directly, rather than returning only the source page.
Content Generation
LLM pipelines for marketing copy, technical documentation, and internal knowledge, with style and quality guardrails throughout.
Code Assistance
Internal tooling that augments your engineering team without compromising the rigor of code review and architectural standards.
NL Data Queries
Plain-language access to dashboards and warehouses, with full audit trails on every query and every result returned.
Anomaly Detection
Continuous monitoring for fraud, system anomalies, and operational outliers across the signals that matter to the business.
Forecasting
Demand, revenue, and capacity forecasting with the underlying uncertainty quantified and presented honestly.
From assessment to operations.
A four-phase rhythm refined across dozens of engagements, designed to ship working systems rather than to bill hours.
Readiness
A two-week scan covering data, processes, infrastructure, and the agentic opportunities most likely to create real value for your business.
Architecture
We design the system end to end, including model selection, retrieval strategy, evaluation harness, and integrations, before any production code is written.
Build
Hands-on delivery, with observability and guardrails built into the system from the very first commit rather than added later.
Operate
Evaluations, drift monitoring, and ongoing improvement. AI is software, and it has to be operated as such.
Recent client outcomes.
A snapshot of recent AI work, with results measured in production.
Common questions.
The questions clients ask most often. If yours is not here, please ask.
What is actually in an AI Readiness Assessment?
A two-week, fixed-scope engagement. The deliverables include an executive scorecard across data, processes, infrastructure, and team readiness; an ROI roadmap with clear sequencing; the three highest-value agentic use cases prioritized for your business; and an architecture and risk review. You leave the engagement with a presentation deck and a written report that your leadership team can act on within the same week.
Are you building from scratch or fine-tuning models?
Most of our work involves building agentic systems on top of frontier models such as Claude, GPT, and Gemini, paired with retrieval, tool use, and a serious evaluation harness. Fine-tuning is the right answer in roughly ten percent of cases, and we will be straightforward with you when it is not. The other ninety percent of value tends to come from retrieval done well, sound integrations, and rigorous evaluation.
How do you handle AI governance and safety?
Guardrails, output validation, and human-in-the-loop checkpoints are designed at the architecture stage, rather than bolted on afterwards. For organizations operating in regulated industries such as healthcare and financial services, we map the system to your compliance posture, including HIPAA, SOC 2, and the EU AI Act, and document the risk controls accordingly.
Can you integrate with our existing CRM, ERP, or Slack?
Yes. In practice, this is most of what shipped agentic AI looks like. We have integrated with Salesforce, HubSpot, Zendesk, Slack, Microsoft Graph, custom internal APIs, and a wide range of legacy systems. The last mile of wiring AI into the systems your team already relies on is where most of the value compounds.
How do you measure whether an AI feature is actually working?
Evaluation begins on day one. We build an evaluation harness alongside the system itself, including task-level rubrics, regression tests for prompts and tool flows, and ongoing observability through traces using Langfuse, Helicone, or whichever stack you prefer. A working demonstration is not a measurement we are willing to rely on in production.
What is the engagement model?
There are three. Fixed-scope productized offers, including the Readiness Assessment and an agent MVP. Retainers for ongoing AI work, which is common once the first agent has shipped. Embedded teams for multi-quarter platform initiatives. We recommend the model that best fits the work during the first conversation.
A two-week assessment, a plan you can act on.
You leave with an executive scorecard, an ROI roadmap, and the three highest-value agentic opportunities prioritized for your business, in a deliverable your leadership team can act on the same week.