Sales Tools.

PAIR Systems · Active Pursuit PAIR Systems builds GoodMem, the autopilot memory layer for agentic AI. GoodMem self-tunes against the customer's own production traces, so accuracy compounds across systems and over time. Agent Tuner adjusts retrieval continuously, without a per-engagement ML project to staff. Client agents become measurably more accurate, cheaper to run, and reliable enough to trust with real workloads. Most enterprise AI projects stall at PoC because the surrounding system is hand-rolled. GoodMem replaces that work with software. Why this is a pursuit: every Slalom client with an AI mandate needs this layer and most don't know it exists yet. Software is GoodMem, services is Slalom. Clean revenue split, no channel conflict. The GoodMem license appears as a line item on Slalom's contract with the client, marked up however Slalom decides. Existing GoodMem customers and deployments include a Fortune 50 semiconductor, Incorta, Wanclouds, ServiceUp, the Department of Energy, and the Google ADK ecosystem. Ask: introductions to Account Managers whose books overlap PAIR's pipeline. Technical validation by James. One lead client to launch the joint motion. Contact: Ahmed Abbasi, GTM, PAIR Systems (ahmed.abbasi@pairsys.ai).

PAIR Systems · Active Pursuit (Data Practice angle) PAIR Systems builds GoodMem, the autopilot memory layer that makes natural-language analytics actually work in production. GoodMem sits between the user's question and the model; Agent Tuner adjusts retrieval against the client's schema, query history, and prior outcomes; verification fires before any query executes. Text-to-SQL accuracy moves from the typical 50 to 65% baseline into the 90s, and accuracy compounds across systems and over time. Live proof point: Incorta, running GoodMem with measured double-digit accuracy gains and MRR improvement on the public CRUMB benchmark. Why this is a pursuit for the data practice: every Slalom data client has a CEO asking for "ChatGPT for our data." The current GSI playbook is stalling. GoodMem is the engine that closes the gap. Slalom owns the warehouse work, integration, change management, governance, and use-case expansion on top of the platform. GoodMem is a line item on Slalom's contract with the client. Ask: introductions to data-practice Account Managers. One client willing to run a 30 to 60-day GoodMem pilot with a measurable accuracy target on a defined warehouse slice. Contact: Ahmed Abbasi, GTM, PAIR Systems (ahmed.abbasi@pairsys.ai).

PAIR Systems · Active Pursuit (Regulated / Federal angle) PAIR Systems builds GoodMem, the autopilot memory layer for agentic AI in regulated environments. GoodMem self-tunes against the customer's own production traces; Agent Tuner adjusts retrieval continuously without a per-engagement ML project to staff. The whole stack runs model-agnostic against open-weight LLMs inside the client's VPC. That architecture matters for FedRAMP, HIPAA, and air-gapped deployments where buyers can't send data to third-party APIs and can't ship agents that quietly drift. Existing GoodMem deployments span a Fortune 50 semiconductor and the Google ADK ecosystem. Why this is a pursuit for federal and regulated practices: clients in this segment need an auditable autopilot memory layer running on infrastructure they control. Most GSIs are still selling ChatGPT wrappers. GoodMem is the alternative architecture these buyers actually need. Software margin for Slalom on top of a scoped services engagement. Ask: introductions to Account Managers in federal, healthcare, financial services, and regulated manufacturing. Technical validation by James. Contact: Ahmed Abbasi, GTM, PAIR Systems (ahmed.abbasi@pairsys.ai).